{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "import os\n",
    "from collections import defaultdict\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "from IPython.display import display\n",
    "import matplotlib\n",
    "\n",
    "plt.rcParams[\"font.family\"] = \"Times New Roman\"\n",
    "plt.rcParams[\"mathtext.fontset\"] = \"cm\"\n",
    "\n",
    "matplotlib.rcParams[\"pdf.fonttype\"] = 42\n",
    "matplotlib.rcParams[\"ps.fonttype\"] = 42"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>method</th>\n",
       "      <th>average</th>\n",
       "      <th>num_params</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Pretrained</td>\n",
       "      <td>48.2</td>\n",
       "      <td>87456000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Simple Average</td>\n",
       "      <td>66.5</td>\n",
       "      <td>87456000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Task Arithmetic</td>\n",
       "      <td>68.0</td>\n",
       "      <td>87456000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ties-Merging</td>\n",
       "      <td>72.2</td>\n",
       "      <td>87456000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Fisher Merging</td>\n",
       "      <td>70.6</td>\n",
       "      <td>87456000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>RegMean</td>\n",
       "      <td>80.5</td>\n",
       "      <td>87456000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Layer-Wise AdaMerging</td>\n",
       "      <td>82.6</td>\n",
       "      <td>87456000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Weight-Ensembling MoE</td>\n",
       "      <td>89.2</td>\n",
       "      <td>547970000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  method  average   num_params\n",
       "0             Pretrained     48.2   87456000.0\n",
       "1         Simple Average     66.5   87456000.0\n",
       "2        Task Arithmetic     68.0   87456000.0\n",
       "3           Ties-Merging     72.2   87456000.0\n",
       "4         Fisher Merging     70.6   87456000.0\n",
       "5                RegMean     80.5   87456000.0\n",
       "6  Layer-Wise AdaMerging     82.6   87456000.0\n",
       "7  Weight-Ensembling MoE     89.2  547970000.0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "baselines = pd.DataFrame(\n",
    "    {\n",
    "        \"method\": [\n",
    "            \"Pretrained\",\n",
    "            # \"Individuals\",\n",
    "            \"Simple Average\",\n",
    "            \"Task Arithmetic\",\n",
    "            \"Ties-Merging\",\n",
    "            \"Fisher Merging\",\n",
    "            \"RegMean\",\n",
    "            \"Layer-Wise AdaMerging\",\n",
    "            \"Weight-Ensembling MoE\",\n",
    "        ],\n",
    "        \"average\": [\n",
    "            48.2,\n",
    "            # 90.3,\n",
    "            66.5,\n",
    "            68.0,\n",
    "            72.2,\n",
    "            70.6,\n",
    "            80.5,\n",
    "            82.6,\n",
    "            89.2,\n",
    "        ],\n",
    "        \"num_params\": [\n",
    "            87456000,\n",
    "            # 87456000,\n",
    "            87456000,\n",
    "            87456000,\n",
    "            87456000,\n",
    "            87456000,\n",
    "            87456000,\n",
    "            87456000,\n",
    "            547.97 * 1000_000,\n",
    "        ],\n",
    "    }\n",
    ")\n",
    "display(baselines)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "#T_70445_row1_col3, #T_70445_row8_col3, #T_70445_row11_col11 {\n",
       "  background-color: #2da155;\n",
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       "#T_70445_row1_col4, #T_70445_row8_col5 {\n",
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       "  background-color: #fdbf6f;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row1_col7, #T_70445_row44_col4, #T_70445_row65_col4 {\n",
       "  background-color: #e2f397;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row1_col8, #T_70445_row10_col9, #T_70445_row12_col4, #T_70445_row26_col10, #T_70445_row33_col10, #T_70445_row54_col10 {\n",
       "  background-color: #199750;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row1_col9 {\n",
       "  background-color: #ecf7a6;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row1_col10, #T_70445_row57_col10, #T_70445_row71_col7 {\n",
       "  background-color: #f88c51;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row1_col11 {\n",
       "  background-color: #fafdb8;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row2_col0, #T_70445_row9_col0, #T_70445_row16_col0, #T_70445_row29_col0 {\n",
       "  background-color: #ab0626;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row2_col2, #T_70445_row9_col2, #T_70445_row16_col2, #T_70445_row23_col2, #T_70445_row30_col2, #T_70445_row37_col2, #T_70445_row44_col2, #T_70445_row51_col2, #T_70445_row56_col10, #T_70445_row58_col2, #T_70445_row63_col10, #T_70445_row65_col2, #T_70445_row72_col2 {\n",
       "  background-color: #e0422f;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row2_col3, #T_70445_row10_col7, #T_70445_row13_col10, #T_70445_row24_col3, #T_70445_row25_col11, #T_70445_row36_col3, #T_70445_row57_col3 {\n",
       "  background-color: #108647;\n",
       "  color: #f1f1f1;\n",
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       "#T_70445_row2_col4, #T_70445_row65_col10 {\n",
       "  background-color: #fff1a8;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row2_col5, #T_70445_row22_col4, #T_70445_row73_col4 {\n",
       "  background-color: #fed481;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row2_col6, #T_70445_row4_col2, #T_70445_row11_col2, #T_70445_row18_col2, #T_70445_row25_col2, #T_70445_row29_col5, #T_70445_row32_col2, #T_70445_row39_col2, #T_70445_row46_col2, #T_70445_row53_col2, #T_70445_row60_col2, #T_70445_row67_col2, #T_70445_row74_col2 {\n",
       "  background-color: #feffbe;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row2_col7, #T_70445_row9_col6, #T_70445_row35_col6 {\n",
       "  background-color: #afdd70;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row2_col8, #T_70445_row17_col7, #T_70445_row19_col11, #T_70445_row22_col8, #T_70445_row25_col3, #T_70445_row33_col4, #T_70445_row43_col3, #T_70445_row58_col7, #T_70445_row66_col5, #T_70445_row67_col6, #T_70445_row68_col6, #T_70445_row69_col6 {\n",
       "  background-color: #0d8044;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row2_col9, #T_70445_row28_col6, #T_70445_row63_col7 {\n",
       "  background-color: #96d268;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row2_col10, #T_70445_row21_col9 {\n",
       "  background-color: #fed884;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row2_col11, #T_70445_row14_col7 {\n",
       "  background-color: #bfe47a;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row3_col0, #T_70445_row10_col0, #T_70445_row17_col0 {\n",
       "  background-color: #b50f26;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row3_col2, #T_70445_row10_col2, #T_70445_row17_col2, #T_70445_row24_col2, #T_70445_row31_col2, #T_70445_row38_col2, #T_70445_row45_col2, #T_70445_row52_col2, #T_70445_row59_col2, #T_70445_row66_col2, #T_70445_row73_col2 {\n",
       "  background-color: #f99153;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row3_col3, #T_70445_row12_col7, #T_70445_row24_col7, #T_70445_row25_col9, #T_70445_row26_col11, #T_70445_row32_col9, #T_70445_row38_col7, #T_70445_row39_col11, #T_70445_row43_col8, #T_70445_row55_col10, #T_70445_row57_col8, #T_70445_row60_col9, #T_70445_row62_col10, #T_70445_row67_col9, #T_70445_row68_col9 {\n",
       "  background-color: #0a7b41;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row3_col4, #T_70445_row5_col5, #T_70445_row8_col11, #T_70445_row50_col9, #T_70445_row73_col3 {\n",
       "  background-color: #d3ec87;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row3_col5 {\n",
       "  background-color: #fbfdba;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row3_col6, #T_70445_row48_col0 {\n",
       "  background-color: #d7ee8a;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row3_col8, #T_70445_row4_col3, #T_70445_row12_col3, #T_70445_row13_col3, #T_70445_row18_col7, #T_70445_row45_col7, #T_70445_row58_col3, #T_70445_row66_col3, #T_70445_row67_col11 {\n",
       "  background-color: #08773f;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row3_col9, #T_70445_row6_col4, #T_70445_row37_col11, #T_70445_row49_col3 {\n",
       "  background-color: #42ac5a;\n",
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       "}\n",
       "#T_70445_row3_col10, #T_70445_row42_col11, #T_70445_row49_col11, #T_70445_row56_col11 {\n",
       "  background-color: #eef8a8;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row3_col11, #T_70445_row17_col4 {\n",
       "  background-color: #87cb67;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row4_col4, #T_70445_row17_col5, #T_70445_row36_col11, #T_70445_row64_col11 {\n",
       "  background-color: #98d368;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row4_col5, #T_70445_row49_col6 {\n",
       "  background-color: #daf08d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row4_col6, #T_70445_row42_col6, #T_70445_row57_col5, #T_70445_row74_col11 {\n",
       "  background-color: #c7e77f;\n",
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       "}\n",
       "#T_70445_row4_col7, #T_70445_row9_col9, #T_70445_row19_col5, #T_70445_row37_col9, #T_70445_row66_col4 {\n",
       "  background-color: #6bbf64;\n",
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       "}\n",
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       "  background-color: #07753e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row4_col9, #T_70445_row33_col5 {\n",
       "  background-color: #219c52;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row4_col10 {\n",
       "  background-color: #b3df72;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row4_col11, #T_70445_row5_col7 {\n",
       "  background-color: #66bd63;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row5_col0, #T_70445_row12_col0, #T_70445_row53_col0, #T_70445_row70_col6 {\n",
       "  background-color: #e24731;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row5_col2, #T_70445_row12_col2, #T_70445_row19_col2, #T_70445_row20_col9, #T_70445_row20_col10, #T_70445_row26_col2, #T_70445_row27_col4, #T_70445_row27_col9, #T_70445_row32_col6, #T_70445_row33_col2, #T_70445_row33_col8, #T_70445_row34_col8, #T_70445_row34_col9, #T_70445_row39_col8, #T_70445_row40_col2, #T_70445_row40_col8, #T_70445_row41_col3, #T_70445_row41_col8, #T_70445_row46_col3, #T_70445_row46_col8, #T_70445_row47_col2, #T_70445_row47_col3, #T_70445_row47_col6, #T_70445_row47_col8, #T_70445_row48_col3, #T_70445_row48_col6, #T_70445_row48_col8, #T_70445_row48_col11, #T_70445_row53_col6, #T_70445_row53_col8, #T_70445_row54_col2, #T_70445_row54_col3, #T_70445_row54_col6, #T_70445_row54_col7, #T_70445_row54_col8, #T_70445_row55_col3, #T_70445_row55_col6, #T_70445_row55_col7, #T_70445_row55_col8, #T_70445_row55_col11, #T_70445_row60_col8, #T_70445_row61_col2, #T_70445_row61_col7, #T_70445_row61_col8, #T_70445_row62_col5, #T_70445_row62_col7, #T_70445_row62_col8, #T_70445_row62_col11, #T_70445_row68_col2, #T_70445_row68_col7, #T_70445_row68_col8, #T_70445_row69_col5, #T_70445_row69_col7, #T_70445_row69_col8, #T_70445_row70_col1, #T_70445_row71_col1, #T_70445_row72_col1, #T_70445_row73_col1, #T_70445_row74_col1, #T_70445_row75_col1, #T_70445_row75_col2, #T_70445_row76_col0, #T_70445_row76_col1 {\n",
       "  background-color: #006837;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row5_col4 {\n",
       "  background-color: #6ec064;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row5_col6, #T_70445_row24_col10 {\n",
       "  background-color: #c5e67e;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row5_col8, #T_70445_row6_col8, #T_70445_row11_col8, #T_70445_row12_col8, #T_70445_row13_col8, #T_70445_row16_col8, #T_70445_row24_col6, #T_70445_row25_col6, #T_70445_row26_col7, #T_70445_row27_col6, #T_70445_row30_col6, #T_70445_row33_col7, #T_70445_row34_col10, #T_70445_row37_col6, #T_70445_row38_col6, #T_70445_row40_col6, #T_70445_row40_col7, #T_70445_row40_col11, #T_70445_row44_col6, #T_70445_row59_col3, #T_70445_row59_col6, #T_70445_row59_col7, #T_70445_row61_col6, #T_70445_row62_col6, #T_70445_row62_col9, #T_70445_row66_col7, #T_70445_row69_col3, #T_70445_row69_col9, #T_70445_row69_col10 {\n",
       "  background-color: #05713c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row5_col9, #T_70445_row16_col3, #T_70445_row38_col11, #T_70445_row40_col5, #T_70445_row45_col5, #T_70445_row45_col9, #T_70445_row47_col10, #T_70445_row59_col9 {\n",
       "  background-color: #15904c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row5_col10, #T_70445_row28_col3 {\n",
       "  background-color: #75c465;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row5_col11, #T_70445_row12_col10, #T_70445_row16_col9, #T_70445_row39_col10, #T_70445_row46_col10, #T_70445_row64_col6 {\n",
       "  background-color: #54b45f;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row6_col0, #T_70445_row75_col0, #T_70445_row76_col4 {\n",
       "  background-color: #e5f49b;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row6_col5, #T_70445_row8_col9, #T_70445_row11_col5 {\n",
       "  background-color: #cbe982;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row6_col6, #T_70445_row43_col9 {\n",
       "  background-color: #cdea83;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row6_col7, #T_70445_row23_col9, #T_70445_row60_col10 {\n",
       "  background-color: #60ba62;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row6_col9, #T_70445_row8_col8, #T_70445_row18_col6, #T_70445_row18_col11, #T_70445_row19_col6, #T_70445_row41_col5, #T_70445_row53_col9, #T_70445_row61_col4 {\n",
       "  background-color: #128a49;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row6_col10, #T_70445_row25_col4, #T_70445_row60_col4, #T_70445_row63_col8, #T_70445_row67_col4, #T_70445_row74_col8 {\n",
       "  background-color: #33a456;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row6_col11, #T_70445_row15_col3, #T_70445_row65_col5 {\n",
       "  background-color: #48ae5c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row7_col3, #T_70445_row9_col11 {\n",
       "  background-color: #89cc67;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row7_col4, #T_70445_row19_col0, #T_70445_row26_col0, #T_70445_row56_col0, #T_70445_row63_col4 {\n",
       "  background-color: #e34933;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row7_col5, #T_70445_row25_col0, #T_70445_row49_col0 {\n",
       "  background-color: #c82227;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row7_col6, #T_70445_row63_col5 {\n",
       "  background-color: #fece7c;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row7_col7, #T_70445_row30_col4, #T_70445_row37_col4, #T_70445_row41_col0 {\n",
       "  background-color: #ddf191;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row7_col8, #T_70445_row31_col4, #T_70445_row72_col8 {\n",
       "  background-color: #70c164;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row7_col10 {\n",
       "  background-color: #dc3b2c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row7_col11, #T_70445_row68_col0 {\n",
       "  background-color: #fee797;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row8_col4, #T_70445_row66_col0 {\n",
       "  background-color: #fdb768;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row8_col6, #T_70445_row28_col11, #T_70445_row36_col5, #T_70445_row73_col5, #T_70445_row75_col4 {\n",
       "  background-color: #f4fab0;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row8_col7, #T_70445_row24_col5, #T_70445_row53_col10, #T_70445_row75_col7 {\n",
       "  background-color: #73c264;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row8_col10 {\n",
       "  background-color: #f67f4b;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row9_col3, #T_70445_row11_col9, #T_70445_row20_col6, #T_70445_row31_col9, #T_70445_row40_col4, #T_70445_row45_col11, #T_70445_row52_col11, #T_70445_row59_col11, #T_70445_row65_col6, #T_70445_row66_col11 {\n",
       "  background-color: #118848;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row9_col4, #T_70445_row63_col11 {\n",
       "  background-color: #f8fcb6;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row9_col5, #T_70445_row44_col10, #T_70445_row73_col0, #T_70445_row74_col4 {\n",
       "  background-color: #fff3ac;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row9_col7, #T_70445_row35_col8, #T_70445_row39_col4, #T_70445_row42_col8, #T_70445_row49_col8, #T_70445_row76_col8 {\n",
       "  background-color: #2aa054;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row9_col8, #T_70445_row11_col3, #T_70445_row12_col9, #T_70445_row13_col7, #T_70445_row20_col11, #T_70445_row30_col3, #T_70445_row41_col10, #T_70445_row46_col11, #T_70445_row50_col8, #T_70445_row51_col6, #T_70445_row53_col11, #T_70445_row61_col9 {\n",
       "  background-color: #097940;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row9_col10, #T_70445_row56_col9 {\n",
       "  background-color: #fee08b;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row10_col3, #T_70445_row11_col7, #T_70445_row13_col4, #T_70445_row19_col3, #T_70445_row20_col3, #T_70445_row31_col7, #T_70445_row36_col8, #T_70445_row39_col9, #T_70445_row47_col5, #T_70445_row58_col6, #T_70445_row64_col8 {\n",
       "  background-color: #0b7d42;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row10_col4, #T_70445_row14_col3, #T_70445_row42_col7 {\n",
       "  background-color: #a0d669;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row10_col5, #T_70445_row13_col0, #T_70445_row20_col0, #T_70445_row27_col0 {\n",
       "  background-color: #e3f399;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row10_col10, #T_70445_row43_col5 {\n",
       "  background-color: #dff293;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row10_col11, #T_70445_row31_col5, #T_70445_row51_col5 {\n",
       "  background-color: #4eb15d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row11_col4, #T_70445_row15_col7, #T_70445_row22_col3 {\n",
       "  background-color: #4bb05c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row11_col10, #T_70445_row29_col11, #T_70445_row49_col7 {\n",
       "  background-color: #9bd469;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row12_col5, #T_70445_row22_col9, #T_70445_row75_col5 {\n",
       "  background-color: #c1e57b;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row12_col6 {\n",
       "  background-color: #8ccd67;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row12_col11, #T_70445_row24_col11, #T_70445_row52_col9, #T_70445_row61_col10 {\n",
       "  background-color: #1b9950;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row13_col5, #T_70445_row63_col1, #T_70445_row64_col1, #T_70445_row65_col1, #T_70445_row66_col1, #T_70445_row67_col1, #T_70445_row68_col1, #T_70445_row69_col1, #T_70445_row75_col11 {\n",
       "  background-color: #b7e075;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row13_col6, #T_70445_row30_col5, #T_70445_row43_col11, #T_70445_row50_col11, #T_70445_row56_col7 {\n",
       "  background-color: #93d168;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row13_col9, #T_70445_row20_col7, #T_70445_row26_col6, #T_70445_row27_col11, #T_70445_row33_col11, #T_70445_row37_col3, #T_70445_row39_col6, #T_70445_row39_col7, #T_70445_row48_col9, #T_70445_row52_col7, #T_70445_row55_col4, #T_70445_row60_col5, #T_70445_row62_col4, #T_70445_row68_col3, #T_70445_row69_col4 {\n",
       "  background-color: #06733d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row13_col11, #T_70445_row24_col9, #T_70445_row29_col3, #T_70445_row29_col6, #T_70445_row40_col10 {\n",
       "  background-color: #16914d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row14_col4 {\n",
       "  background-color: #eb5a3a;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row14_col5 {\n",
       "  background-color: #f67a49;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row14_col6 {\n",
       "  background-color: #a2d76a;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row14_col8, #T_70445_row65_col11, #T_70445_row75_col6 {\n",
       "  background-color: #3ca959;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row14_col9, #T_70445_row42_col9, #T_70445_row63_col9 {\n",
       "  background-color: #fede89;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row14_col10, #T_70445_row28_col10, #T_70445_row35_col4 {\n",
       "  background-color: #ed5f3c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row14_col11, #T_70445_row74_col0 {\n",
       "  background-color: #fffebe;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row15_col4, #T_70445_row50_col4 {\n",
       "  background-color: #fdc574;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row15_col5 {\n",
       "  background-color: #fee18d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row15_col6, #T_70445_row18_col10, #T_70445_row44_col5, #T_70445_row67_col10, #T_70445_row73_col6 {\n",
       "  background-color: #5db961;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row15_col8, #T_70445_row17_col3, #T_70445_row19_col4, #T_70445_row44_col7, #T_70445_row46_col5, #T_70445_row47_col4 {\n",
       "  background-color: #0f8446;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row15_col9, #T_70445_row21_col3, #T_70445_row74_col3 {\n",
       "  background-color: #bde379;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row15_col10, #T_70445_row43_col10, #T_70445_row61_col0, #T_70445_row64_col10 {\n",
       "  background-color: #fba35c;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row15_col11, #T_70445_row21_col7, #T_70445_row23_col5, #T_70445_row38_col10 {\n",
       "  background-color: #b5df74;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row16_col4, #T_70445_row58_col4 {\n",
       "  background-color: #e9f6a1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row16_col5 {\n",
       "  background-color: #dcf08f;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row16_col6, #T_70445_row22_col6, #T_70445_row38_col9, #T_70445_row39_col5 {\n",
       "  background-color: #1e9a51;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row16_col7, #T_70445_row23_col3, #T_70445_row36_col6, #T_70445_row43_col6, #T_70445_row64_col3, #T_70445_row66_col9, #T_70445_row68_col10 {\n",
       "  background-color: #17934e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row16_col10 {\n",
       "  background-color: #fffbb8;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row16_col11, #T_70445_row20_col5, #T_70445_row32_col10, #T_70445_row44_col9, #T_70445_row76_col7 {\n",
       "  background-color: #63bc62;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row17_col6, #T_70445_row23_col7, #T_70445_row30_col7, #T_70445_row37_col7, #T_70445_row54_col4 {\n",
       "  background-color: #138c4a;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row17_col8, #T_70445_row18_col8, #T_70445_row19_col8, #T_70445_row25_col8, #T_70445_row31_col8, #T_70445_row33_col3, #T_70445_row34_col3, #T_70445_row34_col11, #T_70445_row38_col3, #T_70445_row41_col4, #T_70445_row41_col11, #T_70445_row45_col8, #T_70445_row48_col7, #T_70445_row52_col8, #T_70445_row53_col7, #T_70445_row59_col8, #T_70445_row61_col5, #T_70445_row66_col8 {\n",
       "  background-color: #026c39;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row17_col9, #T_70445_row19_col10, #T_70445_row31_col11, #T_70445_row68_col4 {\n",
       "  background-color: #148e4b;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row17_col10, #T_70445_row29_col9, #T_70445_row36_col9, #T_70445_row55_col0 {\n",
       "  background-color: #c3e67d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row17_col11, #T_70445_row28_col8, #T_70445_row32_col4, #T_70445_row50_col6, #T_70445_row50_col7, #T_70445_row64_col7 {\n",
       "  background-color: #279f53;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row18_col3, #T_70445_row26_col3, #T_70445_row27_col3, #T_70445_row29_col8, #T_70445_row32_col11, #T_70445_row50_col3, #T_70445_row54_col9, #T_70445_row65_col3, #T_70445_row65_col7 {\n",
       "  background-color: #0c7f43;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row18_col4, #T_70445_row21_col8, #T_70445_row32_col5, #T_70445_row43_col7, #T_70445_row46_col4, #T_70445_row56_col8, #T_70445_row75_col8, #T_70445_row76_col6 {\n",
       "  background-color: #30a356;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row18_col5 {\n",
       "  background-color: #78c565;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row19_col9, #T_70445_row20_col4, #T_70445_row26_col8, #T_70445_row27_col8, #T_70445_row31_col6, #T_70445_row32_col8, #T_70445_row33_col6, #T_70445_row34_col4, #T_70445_row34_col6, #T_70445_row38_col8, #T_70445_row39_col3, #T_70445_row40_col3, #T_70445_row45_col3, #T_70445_row45_col6, #T_70445_row46_col6, #T_70445_row52_col3, #T_70445_row53_col3, #T_70445_row55_col5, #T_70445_row60_col7, #T_70445_row67_col7, #T_70445_row67_col8, #T_70445_row68_col5, #T_70445_row69_col11 {\n",
       "  background-color: #016a38;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row20_col8, #T_70445_row24_col8, #T_70445_row26_col9, #T_70445_row27_col10, #T_70445_row30_col8, #T_70445_row32_col3, #T_70445_row37_col8, #T_70445_row41_col6, #T_70445_row47_col7, #T_70445_row47_col11, #T_70445_row48_col4, #T_70445_row48_col10, #T_70445_row51_col8, #T_70445_row52_col6, #T_70445_row54_col5, #T_70445_row54_col11, #T_70445_row60_col3, #T_70445_row61_col3, #T_70445_row61_col11, #T_70445_row62_col3, #T_70445_row65_col8 {\n",
       "  background-color: #036e3a;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row21_col1, #T_70445_row22_col0, #T_70445_row22_col1, #T_70445_row23_col1, #T_70445_row24_col1, #T_70445_row25_col1, #T_70445_row26_col1, #T_70445_row27_col1, #T_70445_row28_col0 {\n",
       "  background-color: #a90426;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row21_col4, #T_70445_row21_col10, #T_70445_row49_col4 {\n",
       "  background-color: #e95538;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row21_col5 {\n",
       "  background-color: #f67c4a;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row21_col6 {\n",
       "  background-color: #8ecf67;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row21_col11 {\n",
       "  background-color: #fffdbc;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row22_col5 {\n",
       "  background-color: #fff6b0;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row22_col7, #T_70445_row26_col5, #T_70445_row53_col4 {\n",
       "  background-color: #3faa59;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row22_col10, #T_70445_row65_col0, #T_70445_row71_col3 {\n",
       "  background-color: #fdad60;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row22_col11, #T_70445_row35_col7, #T_70445_row73_col7, #T_70445_row76_col11 {\n",
       "  background-color: #a9da6c;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row23_col0, #T_70445_row35_col0 {\n",
       "  background-color: #ad0826;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row23_col4, #T_70445_row51_col4, #T_70445_row73_col11 {\n",
       "  background-color: #e6f59d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row23_col8, #T_70445_row27_col7, #T_70445_row31_col3, #T_70445_row33_col9, #T_70445_row34_col7, #T_70445_row40_col9, #T_70445_row41_col7, #T_70445_row41_col9, #T_70445_row44_col3, #T_70445_row44_col8, #T_70445_row46_col7, #T_70445_row51_col3, #T_70445_row58_col8, #T_70445_row60_col6, #T_70445_row67_col5, #T_70445_row68_col11 {\n",
       "  background-color: #04703b;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row23_col10 {\n",
       "  background-color: #fff5ae;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row23_col11, #T_70445_row51_col9, #T_70445_row56_col3 {\n",
       "  background-color: #57b65f;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row25_col5, #T_70445_row35_col3, #T_70445_row58_col9, #T_70445_row73_col8 {\n",
       "  background-color: #51b35e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row25_col10, #T_70445_row65_col9 {\n",
       "  background-color: #69be63;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row26_col4, #T_70445_row46_col9, #T_70445_row51_col7, #T_70445_row52_col5, #T_70445_row59_col5, #T_70445_row66_col6 {\n",
       "  background-color: #0e8245;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row27_col5, #T_70445_row57_col6 {\n",
       "  background-color: #36a657;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row28_col1, #T_70445_row29_col1, #T_70445_row30_col0, #T_70445_row30_col1, #T_70445_row31_col1, #T_70445_row32_col1, #T_70445_row33_col1, #T_70445_row34_col1, #T_70445_row36_col0 {\n",
       "  background-color: #af0926;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row28_col4 {\n",
       "  background-color: #f46d43;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row28_col5, #T_70445_row72_col4 {\n",
       "  background-color: #f98e52;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row28_col7, #T_70445_row75_col3, #T_70445_row76_col3 {\n",
       "  background-color: #b1de71;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row28_col9, #T_70445_row49_col9, #T_70445_row74_col9 {\n",
       "  background-color: #fee491;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row29_col7, #T_70445_row36_col7, #T_70445_row38_col5, #T_70445_row44_col11, #T_70445_row51_col11, #T_70445_row58_col11, #T_70445_row69_col0, #T_70445_row74_col6 {\n",
       "  background-color: #39a758;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row29_col10 {\n",
       "  background-color: #fdb365;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row30_col9 {\n",
       "  background-color: #5ab760;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row30_col10 {\n",
       "  background-color: #fffcba;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row30_col11, #T_70445_row42_col3, #T_70445_row58_col5 {\n",
       "  background-color: #45ad5b;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row31_col0, #T_70445_row35_col1, #T_70445_row36_col1, #T_70445_row37_col1, #T_70445_row38_col1, #T_70445_row39_col1, #T_70445_row40_col1, #T_70445_row41_col1, #T_70445_row43_col0 {\n",
       "  background-color: #b91326;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row31_col10, #T_70445_row76_col5 {\n",
       "  background-color: #b9e176;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row32_col0, #T_70445_row50_col0, #T_70445_row71_col10 {\n",
       "  background-color: #ca2427;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row33_col0, #T_70445_row57_col0 {\n",
       "  background-color: #e44c34;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row34_col0 {\n",
       "  background-color: #e0f295;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row34_col5 {\n",
       "  background-color: #18954f;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row35_col5, #T_70445_row63_col0 {\n",
       "  background-color: #fca55d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row35_col9 {\n",
       "  background-color: #fee695;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row35_col10 {\n",
       "  background-color: #e65036;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row35_col11 {\n",
       "  background-color: #eff8aa;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row36_col4, #T_70445_row49_col5 {\n",
       "  background-color: #fecc7b;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row36_col10 {\n",
       "  background-color: #fcaa5f;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row37_col0 {\n",
       "  background-color: #b30d26;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row37_col10 {\n",
       "  background-color: #fff2aa;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row38_col0, #T_70445_row44_col0 {\n",
       "  background-color: #bd1726;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row38_col4, #T_70445_row45_col4, #T_70445_row63_col3, #T_70445_row76_col10 {\n",
       "  background-color: #7ac665;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row39_col0, #T_70445_row42_col1, #T_70445_row43_col1, #T_70445_row44_col1, #T_70445_row45_col1, #T_70445_row46_col1, #T_70445_row47_col1, #T_70445_row48_col1, #T_70445_row51_col0 {\n",
       "  background-color: #ce2827;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row40_col0, #T_70445_row58_col0 {\n",
       "  background-color: #e75337;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row42_col4, #T_70445_row56_col4 {\n",
       "  background-color: #ee613e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row42_col5 {\n",
       "  background-color: #fdbb6c;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row42_col10 {\n",
       "  background-color: #e54e35;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row43_col4, #T_70445_row67_col0 {\n",
       "  background-color: #fec877;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row45_col10 {\n",
       "  background-color: #addc6f;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row47_col0, #T_70445_row59_col0 {\n",
       "  background-color: #ec5c3b;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row49_col1, #T_70445_row50_col1, #T_70445_row51_col1, #T_70445_row52_col1, #T_70445_row53_col1, #T_70445_row54_col1, #T_70445_row55_col1 {\n",
       "  background-color: #ea5739;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row49_col10 {\n",
       "  background-color: #db382b;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row50_col5, #T_70445_row64_col5, #T_70445_row64_col9, #T_70445_row71_col8 {\n",
       "  background-color: #cfeb85;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row50_col10 {\n",
       "  background-color: #f88950;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row51_col10, #T_70445_row70_col0, #T_70445_row72_col11 {\n",
       "  background-color: #feea9b;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row52_col4 {\n",
       "  background-color: #7fc866;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row52_col10, #T_70445_row57_col9, #T_70445_row59_col10 {\n",
       "  background-color: #c9e881;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row54_col0, #T_70445_row60_col0 {\n",
       "  background-color: #f57245;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row56_col5, #T_70445_row73_col10 {\n",
       "  background-color: #fed683;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row56_col6, #T_70445_row71_col6 {\n",
       "  background-color: #e8f59f;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row57_col4, #T_70445_row64_col4 {\n",
       "  background-color: #fdc171;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row57_col7 {\n",
       "  background-color: #249d53;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row58_col10 {\n",
       "  background-color: #feefa3;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row59_col4 {\n",
       "  background-color: #7dc765;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row62_col0, #T_70445_row72_col6 {\n",
       "  background-color: #9dd569;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row63_col6 {\n",
       "  background-color: #feec9f;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row64_col0 {\n",
       "  background-color: #fca85e;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row66_col10, #T_70445_row75_col10 {\n",
       "  background-color: #bbe278;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row71_col0 {\n",
       "  background-color: #feeb9d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row71_col4 {\n",
       "  background-color: #da362a;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row71_col9 {\n",
       "  background-color: #dd3d2d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row71_col11 {\n",
       "  background-color: #f8864f;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row72_col0 {\n",
       "  background-color: #feeda1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row72_col3 {\n",
       "  background-color: #f2faae;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row72_col7, #T_70445_row74_col10 {\n",
       "  background-color: #f1f9ac;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row72_col9 {\n",
       "  background-color: #f47044;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row72_col10 {\n",
       "  background-color: #f7814c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_70445_row73_col9 {\n",
       "  background-color: #fdbd6d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row74_col5 {\n",
       "  background-color: #d5ed88;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row74_col7 {\n",
       "  background-color: #84ca66;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row75_col9 {\n",
       "  background-color: #fee999;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_70445_row76_col9 {\n",
       "  background-color: #fff8b4;\n",
       "  color: #000000;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_70445\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_70445_level0_col0\" class=\"col_heading level0 col0\" >num_params</th>\n",
       "      <th id=\"T_70445_level0_col1\" class=\"col_heading level0 col1\" >gate_k</th>\n",
       "      <th id=\"T_70445_level0_col2\" class=\"col_heading level0 col2\" >k</th>\n",
       "      <th id=\"T_70445_level0_col3\" class=\"col_heading level0 col3\" >svhn</th>\n",
       "      <th id=\"T_70445_level0_col4\" class=\"col_heading level0 col4\" >stanford_cars</th>\n",
       "      <th id=\"T_70445_level0_col5\" class=\"col_heading level0 col5\" >resisc45</th>\n",
       "      <th id=\"T_70445_level0_col6\" class=\"col_heading level0 col6\" >eurosat</th>\n",
       "      <th id=\"T_70445_level0_col7\" class=\"col_heading level0 col7\" >gtsrb</th>\n",
       "      <th id=\"T_70445_level0_col8\" class=\"col_heading level0 col8\" >mnist</th>\n",
       "      <th id=\"T_70445_level0_col9\" class=\"col_heading level0 col9\" >dtd</th>\n",
       "      <th id=\"T_70445_level0_col10\" class=\"col_heading level0 col10\" >sun397</th>\n",
       "      <th id=\"T_70445_level0_col11\" class=\"col_heading level0 col11\" >average</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "      <td id=\"T_70445_row0_col0\" class=\"data row0 col0\" >94008576</td>\n",
       "      <td id=\"T_70445_row0_col1\" class=\"data row0 col1\" >1</td>\n",
       "      <td id=\"T_70445_row0_col2\" class=\"data row0 col2\" >4</td>\n",
       "      <td id=\"T_70445_row0_col3\" class=\"data row0 col3\" >0.901621</td>\n",
       "      <td id=\"T_70445_row0_col4\" class=\"data row0 col4\" >0.623057</td>\n",
       "      <td id=\"T_70445_row0_col5\" class=\"data row0 col5\" >0.716667</td>\n",
       "      <td id=\"T_70445_row0_col6\" class=\"data row0 col6\" >0.836667</td>\n",
       "      <td id=\"T_70445_row0_col7\" class=\"data row0 col7\" >0.748298</td>\n",
       "      <td id=\"T_70445_row0_col8\" class=\"data row0 col8\" >0.971300</td>\n",
       "      <td id=\"T_70445_row0_col9\" class=\"data row0 col9\" >0.602128</td>\n",
       "      <td id=\"T_70445_row0_col10\" class=\"data row0 col10\" >0.667758</td>\n",
       "      <td id=\"T_70445_row0_col11\" class=\"data row0 col11\" >75.843684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "      <td id=\"T_70445_row1_col0\" class=\"data row1 col0\" >99316992</td>\n",
       "      <td id=\"T_70445_row1_col1\" class=\"data row1 col1\" >1</td>\n",
       "      <td id=\"T_70445_row1_col2\" class=\"data row1 col2\" >8</td>\n",
       "      <td id=\"T_70445_row1_col3\" class=\"data row1 col3\" >0.935502</td>\n",
       "      <td id=\"T_70445_row1_col4\" class=\"data row1 col4\" >0.656510</td>\n",
       "      <td id=\"T_70445_row1_col5\" class=\"data row1 col5\" >0.759206</td>\n",
       "      <td id=\"T_70445_row1_col6\" class=\"data row1 col6\" >0.886296</td>\n",
       "      <td id=\"T_70445_row1_col7\" class=\"data row1 col7\" >0.827553</td>\n",
       "      <td id=\"T_70445_row1_col8\" class=\"data row1 col8\" >0.986900</td>\n",
       "      <td id=\"T_70445_row1_col9\" class=\"data row1 col9\" >0.663298</td>\n",
       "      <td id=\"T_70445_row1_col10\" class=\"data row1 col10\" >0.680403</td>\n",
       "      <td id=\"T_70445_row1_col11\" class=\"data row1 col11\" >79.945873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "      <td id=\"T_70445_row2_col0\" class=\"data row2 col0\" >109933824</td>\n",
       "      <td id=\"T_70445_row2_col1\" class=\"data row2 col1\" >1</td>\n",
       "      <td id=\"T_70445_row2_col2\" class=\"data row2 col2\" >16</td>\n",
       "      <td id=\"T_70445_row2_col3\" class=\"data row2 col3\" >0.953442</td>\n",
       "      <td id=\"T_70445_row2_col4\" class=\"data row2 col4\" >0.688720</td>\n",
       "      <td id=\"T_70445_row2_col5\" class=\"data row2 col5\" >0.802698</td>\n",
       "      <td id=\"T_70445_row2_col6\" class=\"data row2 col6\" >0.910741</td>\n",
       "      <td id=\"T_70445_row2_col7\" class=\"data row2 col7\" >0.867300</td>\n",
       "      <td id=\"T_70445_row2_col8\" class=\"data row2 col8\" >0.991500</td>\n",
       "      <td id=\"T_70445_row2_col9\" class=\"data row2 col9\" >0.711702</td>\n",
       "      <td id=\"T_70445_row2_col10\" class=\"data row2 col10\" >0.691889</td>\n",
       "      <td id=\"T_70445_row2_col11\" class=\"data row2 col11\" >82.724909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "      <td id=\"T_70445_row3_col0\" class=\"data row3 col0\" >131167488</td>\n",
       "      <td id=\"T_70445_row3_col1\" class=\"data row3 col1\" >1</td>\n",
       "      <td id=\"T_70445_row3_col2\" class=\"data row3 col2\" >32</td>\n",
       "      <td id=\"T_70445_row3_col3\" class=\"data row3 col3\" >0.959473</td>\n",
       "      <td id=\"T_70445_row3_col4\" class=\"data row3 col4\" >0.717572</td>\n",
       "      <td id=\"T_70445_row3_col5\" class=\"data row3 col5\" >0.833175</td>\n",
       "      <td id=\"T_70445_row3_col6\" class=\"data row3 col6\" >0.925926</td>\n",
       "      <td id=\"T_70445_row3_col7\" class=\"data row3 col7\" >0.895962</td>\n",
       "      <td id=\"T_70445_row3_col8\" class=\"data row3 col8\" >0.993000</td>\n",
       "      <td id=\"T_70445_row3_col9\" class=\"data row3 col9\" >0.744681</td>\n",
       "      <td id=\"T_70445_row3_col10\" class=\"data row3 col10\" >0.705844</td>\n",
       "      <td id=\"T_70445_row3_col11\" class=\"data row3 col11\" >84.695406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "      <td id=\"T_70445_row4_col0\" class=\"data row4 col0\" >173634816</td>\n",
       "      <td id=\"T_70445_row4_col1\" class=\"data row4 col1\" >1</td>\n",
       "      <td id=\"T_70445_row4_col2\" class=\"data row4 col2\" >64</td>\n",
       "      <td id=\"T_70445_row4_col3\" class=\"data row4 col3\" >0.962200</td>\n",
       "      <td id=\"T_70445_row4_col4\" class=\"data row4 col4\" >0.737470</td>\n",
       "      <td id=\"T_70445_row4_col5\" class=\"data row4 col5\" >0.852381</td>\n",
       "      <td id=\"T_70445_row4_col6\" class=\"data row4 col6\" >0.930741</td>\n",
       "      <td id=\"T_70445_row4_col7\" class=\"data row4 col7\" >0.908789</td>\n",
       "      <td id=\"T_70445_row4_col8\" class=\"data row4 col8\" >0.993600</td>\n",
       "      <td id=\"T_70445_row4_col9\" class=\"data row4 col9\" >0.756383</td>\n",
       "      <td id=\"T_70445_row4_col10\" class=\"data row4 col10\" >0.716826</td>\n",
       "      <td id=\"T_70445_row4_col11\" class=\"data row4 col11\" >85.729878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "      <td id=\"T_70445_row5_col0\" class=\"data row5 col0\" >258569472</td>\n",
       "      <td id=\"T_70445_row5_col1\" class=\"data row5 col1\" >1</td>\n",
       "      <td id=\"T_70445_row5_col2\" class=\"data row5 col2\" >128</td>\n",
       "      <td id=\"T_70445_row5_col3\" class=\"data row5 col3\" >0.962853</td>\n",
       "      <td id=\"T_70445_row5_col4\" class=\"data row5 col4\" >0.749534</td>\n",
       "      <td id=\"T_70445_row5_col5\" class=\"data row5 col5\" >0.856032</td>\n",
       "      <td id=\"T_70445_row5_col6\" class=\"data row5 col6\" >0.931111</td>\n",
       "      <td id=\"T_70445_row5_col7\" class=\"data row5 col7\" >0.912272</td>\n",
       "      <td id=\"T_70445_row5_col8\" class=\"data row5 col8\" >0.994400</td>\n",
       "      <td id=\"T_70445_row5_col9\" class=\"data row5 col9\" >0.763830</td>\n",
       "      <td id=\"T_70445_row5_col10\" class=\"data row5 col10\" >0.725491</td>\n",
       "      <td id=\"T_70445_row5_col11\" class=\"data row5 col11\" >86.194041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "      <td id=\"T_70445_row6_col0\" class=\"data row6 col0\" >768177408</td>\n",
       "      <td id=\"T_70445_row6_col1\" class=\"data row6 col1\" >1</td>\n",
       "      <td id=\"T_70445_row6_col2\" class=\"data row6 col2\" >-1</td>\n",
       "      <td id=\"T_70445_row6_col3\" class=\"data row6 col3\" >0.963122</td>\n",
       "      <td id=\"T_70445_row6_col4\" class=\"data row6 col4\" >0.759980</td>\n",
       "      <td id=\"T_70445_row6_col5\" class=\"data row6 col5\" >0.859841</td>\n",
       "      <td id=\"T_70445_row6_col6\" class=\"data row6 col6\" >0.928889</td>\n",
       "      <td id=\"T_70445_row6_col7\" class=\"data row6 col7\" >0.914885</td>\n",
       "      <td id=\"T_70445_row6_col8\" class=\"data row6 col8\" >0.994300</td>\n",
       "      <td id=\"T_70445_row6_col9\" class=\"data row6 col9\" >0.767021</td>\n",
       "      <td id=\"T_70445_row6_col10\" class=\"data row6 col10\" >0.733199</td>\n",
       "      <td id=\"T_70445_row6_col11\" class=\"data row6 col11\" >86.515477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "      <td id=\"T_70445_row7_col0\" class=\"data row7 col0\" >94672128</td>\n",
       "      <td id=\"T_70445_row7_col1\" class=\"data row7 col1\" >2</td>\n",
       "      <td id=\"T_70445_row7_col2\" class=\"data row7 col2\" >4</td>\n",
       "      <td id=\"T_70445_row7_col3\" class=\"data row7 col3\" >0.898471</td>\n",
       "      <td id=\"T_70445_row7_col4\" class=\"data row7 col4\" >0.632384</td>\n",
       "      <td id=\"T_70445_row7_col5\" class=\"data row7 col5\" >0.733175</td>\n",
       "      <td id=\"T_70445_row7_col6\" class=\"data row7 col6\" >0.890741</td>\n",
       "      <td id=\"T_70445_row7_col7\" class=\"data row7 col7\" >0.831987</td>\n",
       "      <td id=\"T_70445_row7_col8\" class=\"data row7 col8\" >0.975800</td>\n",
       "      <td id=\"T_70445_row7_col9\" class=\"data row7 col9\" >0.614894</td>\n",
       "      <td id=\"T_70445_row7_col10\" class=\"data row7 col10\" >0.669320</td>\n",
       "      <td id=\"T_70445_row7_col11\" class=\"data row7 col11\" >78.084642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "      <td id=\"T_70445_row8_col0\" class=\"data row8 col0\" >99980544</td>\n",
       "      <td id=\"T_70445_row8_col1\" class=\"data row8 col1\" >2</td>\n",
       "      <td id=\"T_70445_row8_col2\" class=\"data row8 col2\" >8</td>\n",
       "      <td id=\"T_70445_row8_col3\" class=\"data row8 col3\" >0.934773</td>\n",
       "      <td id=\"T_70445_row8_col4\" class=\"data row8 col4\" >0.664097</td>\n",
       "      <td id=\"T_70445_row8_col5\" class=\"data row8 col5\" >0.779841</td>\n",
       "      <td id=\"T_70445_row8_col6\" class=\"data row8 col6\" >0.914815</td>\n",
       "      <td id=\"T_70445_row8_col7\" class=\"data row8 col7\" >0.905463</td>\n",
       "      <td id=\"T_70445_row8_col8\" class=\"data row8 col8\" >0.989400</td>\n",
       "      <td id=\"T_70445_row8_col9\" class=\"data row8 col9\" >0.685106</td>\n",
       "      <td id=\"T_70445_row8_col10\" class=\"data row8 col10\" >0.678690</td>\n",
       "      <td id=\"T_70445_row8_col11\" class=\"data row8 col11\" >81.902312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "      <td id=\"T_70445_row9_col0\" class=\"data row9 col0\" >110597376</td>\n",
       "      <td id=\"T_70445_row9_col1\" class=\"data row9 col1\" >2</td>\n",
       "      <td id=\"T_70445_row9_col2\" class=\"data row9 col2\" >16</td>\n",
       "      <td id=\"T_70445_row9_col3\" class=\"data row9 col3\" >0.951982</td>\n",
       "      <td id=\"T_70445_row9_col4\" class=\"data row9 col4\" >0.700659</td>\n",
       "      <td id=\"T_70445_row9_col5\" class=\"data row9 col5\" >0.822222</td>\n",
       "      <td id=\"T_70445_row9_col6\" class=\"data row9 col6\" >0.937407</td>\n",
       "      <td id=\"T_70445_row9_col7\" class=\"data row9 col7\" >0.942359</td>\n",
       "      <td id=\"T_70445_row9_col8\" class=\"data row9 col8\" >0.992700</td>\n",
       "      <td id=\"T_70445_row9_col9\" class=\"data row9 col9\" >0.729255</td>\n",
       "      <td id=\"T_70445_row9_col10\" class=\"data row9 col10\" >0.693300</td>\n",
       "      <td id=\"T_70445_row9_col11\" class=\"data row9 col11\" >84.623569</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "      <td id=\"T_70445_row10_col0\" class=\"data row10 col0\" >131831040</td>\n",
       "      <td id=\"T_70445_row10_col1\" class=\"data row10 col1\" >2</td>\n",
       "      <td id=\"T_70445_row10_col2\" class=\"data row10 col2\" >32</td>\n",
       "      <td id=\"T_70445_row10_col3\" class=\"data row10 col3\" >0.958282</td>\n",
       "      <td id=\"T_70445_row10_col4\" class=\"data row10 col4\" >0.734983</td>\n",
       "      <td id=\"T_70445_row10_col5\" class=\"data row10 col5\" >0.847143</td>\n",
       "      <td id=\"T_70445_row10_col6\" class=\"data row10 col6\" >0.945185</td>\n",
       "      <td id=\"T_70445_row10_col7\" class=\"data row10 col7\" >0.963816</td>\n",
       "      <td id=\"T_70445_row10_col8\" class=\"data row10 col8\" >0.993500</td>\n",
       "      <td id=\"T_70445_row10_col9\" class=\"data row10 col9\" >0.759574</td>\n",
       "      <td id=\"T_70445_row10_col10\" class=\"data row10 col10\" >0.708967</td>\n",
       "      <td id=\"T_70445_row10_col11\" class=\"data row10 col11\" >86.393142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "      <td id=\"T_70445_row11_col0\" class=\"data row11 col0\" >174298368</td>\n",
       "      <td id=\"T_70445_row11_col1\" class=\"data row11 col1\" >2</td>\n",
       "      <td id=\"T_70445_row11_col2\" class=\"data row11 col2\" >64</td>\n",
       "      <td id=\"T_70445_row11_col3\" class=\"data row11 col3\" >0.960395</td>\n",
       "      <td id=\"T_70445_row11_col4\" class=\"data row11 col4\" >0.757617</td>\n",
       "      <td id=\"T_70445_row11_col5\" class=\"data row11 col5\" >0.860159</td>\n",
       "      <td id=\"T_70445_row11_col6\" class=\"data row11 col6\" >0.944815</td>\n",
       "      <td id=\"T_70445_row11_col7\" class=\"data row11 col7\" >0.971734</td>\n",
       "      <td id=\"T_70445_row11_col8\" class=\"data row11 col8\" >0.994200</td>\n",
       "      <td id=\"T_70445_row11_col9\" class=\"data row11 col9\" >0.768085</td>\n",
       "      <td id=\"T_70445_row11_col10\" class=\"data row11 col10\" >0.720453</td>\n",
       "      <td id=\"T_70445_row11_col11\" class=\"data row11 col11\" >87.218227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "      <td id=\"T_70445_row12_col0\" class=\"data row12 col0\" >259233024</td>\n",
       "      <td id=\"T_70445_row12_col1\" class=\"data row12 col1\" >2</td>\n",
       "      <td id=\"T_70445_row12_col2\" class=\"data row12 col2\" >128</td>\n",
       "      <td id=\"T_70445_row12_col3\" class=\"data row12 col3\" >0.961778</td>\n",
       "      <td id=\"T_70445_row12_col4\" class=\"data row12 col4\" >0.770053</td>\n",
       "      <td id=\"T_70445_row12_col5\" class=\"data row12 col5\" >0.864603</td>\n",
       "      <td id=\"T_70445_row12_col6\" class=\"data row12 col6\" >0.946296</td>\n",
       "      <td id=\"T_70445_row12_col7\" class=\"data row12 col7\" >0.973555</td>\n",
       "      <td id=\"T_70445_row12_col8\" class=\"data row12 col8\" >0.994400</td>\n",
       "      <td id=\"T_70445_row12_col9\" class=\"data row12 col9\" >0.776064</td>\n",
       "      <td id=\"T_70445_row12_col10\" class=\"data row12 col10\" >0.729572</td>\n",
       "      <td id=\"T_70445_row12_col11\" class=\"data row12 col11\" >87.704017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "      <td id=\"T_70445_row13_col0\" class=\"data row13 col0\" >768840960</td>\n",
       "      <td id=\"T_70445_row13_col1\" class=\"data row13 col1\" >2</td>\n",
       "      <td id=\"T_70445_row13_col2\" class=\"data row13 col2\" >-1</td>\n",
       "      <td id=\"T_70445_row13_col3\" class=\"data row13 col3\" >0.962277</td>\n",
       "      <td id=\"T_70445_row13_col4\" class=\"data row13 col4\" >0.779754</td>\n",
       "      <td id=\"T_70445_row13_col5\" class=\"data row13 col5\" >0.868730</td>\n",
       "      <td id=\"T_70445_row13_col6\" class=\"data row13 col6\" >0.944444</td>\n",
       "      <td id=\"T_70445_row13_col7\" class=\"data row13 col7\" >0.975534</td>\n",
       "      <td id=\"T_70445_row13_col8\" class=\"data row13 col8\" >0.994300</td>\n",
       "      <td id=\"T_70445_row13_col9\" class=\"data row13 col9\" >0.779787</td>\n",
       "      <td id=\"T_70445_row13_col10\" class=\"data row13 col10\" >0.739043</td>\n",
       "      <td id=\"T_70445_row13_col11\" class=\"data row13 col11\" >88.048375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "      <td id=\"T_70445_row14_col0\" class=\"data row14 col0\" >95999232</td>\n",
       "      <td id=\"T_70445_row14_col1\" class=\"data row14 col1\" >4</td>\n",
       "      <td id=\"T_70445_row14_col2\" class=\"data row14 col2\" >4</td>\n",
       "      <td id=\"T_70445_row14_col3\" class=\"data row14 col3\" >0.887638</td>\n",
       "      <td id=\"T_70445_row14_col4\" class=\"data row14 col4\" >0.637483</td>\n",
       "      <td id=\"T_70445_row14_col5\" class=\"data row14 col5\" >0.767143</td>\n",
       "      <td id=\"T_70445_row14_col6\" class=\"data row14 col6\" >0.940741</td>\n",
       "      <td id=\"T_70445_row14_col7\" class=\"data row14 col7\" >0.855819</td>\n",
       "      <td id=\"T_70445_row14_col8\" class=\"data row14 col8\" >0.982400</td>\n",
       "      <td id=\"T_70445_row14_col9\" class=\"data row14 col9\" >0.622340</td>\n",
       "      <td id=\"T_70445_row14_col10\" class=\"data row14 col10\" >0.674408</td>\n",
       "      <td id=\"T_70445_row14_col11\" class=\"data row14 col11\" >79.599659</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
       "      <td id=\"T_70445_row15_col0\" class=\"data row15 col0\" >101307648</td>\n",
       "      <td id=\"T_70445_row15_col1\" class=\"data row15 col1\" >4</td>\n",
       "      <td id=\"T_70445_row15_col2\" class=\"data row15 col2\" >8</td>\n",
       "      <td id=\"T_70445_row15_col3\" class=\"data row15 col3\" >0.925476</td>\n",
       "      <td id=\"T_70445_row15_col4\" class=\"data row15 col4\" >0.668822</td>\n",
       "      <td id=\"T_70445_row15_col5\" class=\"data row15 col5\" >0.809365</td>\n",
       "      <td id=\"T_70445_row15_col6\" class=\"data row15 col6\" >0.956296</td>\n",
       "      <td id=\"T_70445_row15_col7\" class=\"data row15 col7\" >0.925336</td>\n",
       "      <td id=\"T_70445_row15_col8\" class=\"data row15 col8\" >0.990500</td>\n",
       "      <td id=\"T_70445_row15_col9\" class=\"data row15 col9\" >0.692021</td>\n",
       "      <td id=\"T_70445_row15_col10\" class=\"data row15 col10\" >0.683275</td>\n",
       "      <td id=\"T_70445_row15_col11\" class=\"data row15 col11\" >83.138654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
       "      <td id=\"T_70445_row16_col0\" class=\"data row16 col0\" >111924480</td>\n",
       "      <td id=\"T_70445_row16_col1\" class=\"data row16 col1\" >4</td>\n",
       "      <td id=\"T_70445_row16_col2\" class=\"data row16 col2\" >16</td>\n",
       "      <td id=\"T_70445_row16_col3\" class=\"data row16 col3\" >0.947180</td>\n",
       "      <td id=\"T_70445_row16_col4\" class=\"data row16 col4\" >0.707375</td>\n",
       "      <td id=\"T_70445_row16_col5\" class=\"data row16 col5\" >0.851905</td>\n",
       "      <td id=\"T_70445_row16_col6\" class=\"data row16 col6\" >0.968518</td>\n",
       "      <td id=\"T_70445_row16_col7\" class=\"data row16 col7\" >0.954394</td>\n",
       "      <td id=\"T_70445_row16_col8\" class=\"data row16 col8\" >0.994400</td>\n",
       "      <td id=\"T_70445_row16_col9\" class=\"data row16 col9\" >0.737766</td>\n",
       "      <td id=\"T_70445_row16_col10\" class=\"data row16 col10\" >0.700554</td>\n",
       "      <td id=\"T_70445_row16_col11\" class=\"data row16 col11\" >85.776159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
       "      <td id=\"T_70445_row17_col0\" class=\"data row17 col0\" >133158144</td>\n",
       "      <td id=\"T_70445_row17_col1\" class=\"data row17 col1\" >4</td>\n",
       "      <td id=\"T_70445_row17_col2\" class=\"data row17 col2\" >32</td>\n",
       "      <td id=\"T_70445_row17_col3\" class=\"data row17 col3\" >0.954556</td>\n",
       "      <td id=\"T_70445_row17_col4\" class=\"data row17 col4\" >0.742445</td>\n",
       "      <td id=\"T_70445_row17_col5\" class=\"data row17 col5\" >0.880952</td>\n",
       "      <td id=\"T_70445_row17_col6\" class=\"data row17 col6\" >0.972963</td>\n",
       "      <td id=\"T_70445_row17_col7\" class=\"data row17 col7\" >0.968567</td>\n",
       "      <td id=\"T_70445_row17_col8\" class=\"data row17 col8\" >0.995200</td>\n",
       "      <td id=\"T_70445_row17_col9\" class=\"data row17 col9\" >0.764362</td>\n",
       "      <td id=\"T_70445_row17_col10\" class=\"data row17 col10\" >0.714207</td>\n",
       "      <td id=\"T_70445_row17_col11\" class=\"data row17 col11\" >87.415642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
       "      <td id=\"T_70445_row18_col0\" class=\"data row18 col0\" >175625472</td>\n",
       "      <td id=\"T_70445_row18_col1\" class=\"data row18 col1\" >4</td>\n",
       "      <td id=\"T_70445_row18_col2\" class=\"data row18 col2\" >64</td>\n",
       "      <td id=\"T_70445_row18_col3\" class=\"data row18 col3\" >0.957091</td>\n",
       "      <td id=\"T_70445_row18_col4\" class=\"data row18 col4\" >0.764333</td>\n",
       "      <td id=\"T_70445_row18_col5\" class=\"data row18 col5\" >0.892857</td>\n",
       "      <td id=\"T_70445_row18_col6\" class=\"data row18 col6\" >0.973704</td>\n",
       "      <td id=\"T_70445_row18_col7\" class=\"data row18 col7\" >0.975930</td>\n",
       "      <td id=\"T_70445_row18_col8\" class=\"data row18 col8\" >0.995200</td>\n",
       "      <td id=\"T_70445_row18_col9\" class=\"data row18 col9\" >0.778723</td>\n",
       "      <td id=\"T_70445_row18_col10\" class=\"data row18 col10\" >0.728363</td>\n",
       "      <td id=\"T_70445_row18_col11\" class=\"data row18 col11\" >88.327517</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
       "      <td id=\"T_70445_row19_col0\" class=\"data row19 col0\" >260560128</td>\n",
       "      <td id=\"T_70445_row19_col1\" class=\"data row19 col1\" >4</td>\n",
       "      <td id=\"T_70445_row19_col2\" class=\"data row19 col2\" >128</td>\n",
       "      <td id=\"T_70445_row19_col3\" class=\"data row19 col3\" >0.958167</td>\n",
       "      <td id=\"T_70445_row19_col4\" class=\"data row19 col4\" >0.776769</td>\n",
       "      <td id=\"T_70445_row19_col5\" class=\"data row19 col5\" >0.897143</td>\n",
       "      <td id=\"T_70445_row19_col6\" class=\"data row19 col6\" >0.973704</td>\n",
       "      <td id=\"T_70445_row19_col7\" class=\"data row19 col7\" >0.977751</td>\n",
       "      <td id=\"T_70445_row19_col8\" class=\"data row19 col8\" >0.995400</td>\n",
       "      <td id=\"T_70445_row19_col9\" class=\"data row19 col9\" >0.785106</td>\n",
       "      <td id=\"T_70445_row19_col10\" class=\"data row19 col10\" >0.737683</td>\n",
       "      <td id=\"T_70445_row19_col11\" class=\"data row19 col11\" >88.771535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
       "      <td id=\"T_70445_row20_col0\" class=\"data row20 col0\" >770168064</td>\n",
       "      <td id=\"T_70445_row20_col1\" class=\"data row20 col1\" >4</td>\n",
       "      <td id=\"T_70445_row20_col2\" class=\"data row20 col2\" >-1</td>\n",
       "      <td id=\"T_70445_row20_col3\" class=\"data row20 col3\" >0.958974</td>\n",
       "      <td id=\"T_70445_row20_col4\" class=\"data row20 col4\" >0.786967</td>\n",
       "      <td id=\"T_70445_row20_col5\" class=\"data row20 col5\" >0.899683</td>\n",
       "      <td id=\"T_70445_row20_col6\" class=\"data row20 col6\" >0.974074</td>\n",
       "      <td id=\"T_70445_row20_col7\" class=\"data row20 col7\" >0.979018</td>\n",
       "      <td id=\"T_70445_row20_col8\" class=\"data row20 col8\" >0.995100</td>\n",
       "      <td id=\"T_70445_row20_col9\" class=\"data row20 col9\" >0.786170</td>\n",
       "      <td id=\"T_70445_row20_col10\" class=\"data row20 col10\" >0.744635</td>\n",
       "      <td id=\"T_70445_row20_col11\" class=\"data row20 col11\" >89.057752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
       "      <td id=\"T_70445_row21_col0\" class=\"data row21 col0\" >98653440</td>\n",
       "      <td id=\"T_70445_row21_col1\" class=\"data row21 col1\" >8</td>\n",
       "      <td id=\"T_70445_row21_col2\" class=\"data row21 col2\" >4</td>\n",
       "      <td id=\"T_70445_row21_col3\" class=\"data row21 col3\" >0.872004</td>\n",
       "      <td id=\"T_70445_row21_col4\" class=\"data row21 col4\" >0.635991</td>\n",
       "      <td id=\"T_70445_row21_col5\" class=\"data row21 col5\" >0.768413</td>\n",
       "      <td id=\"T_70445_row21_col6\" class=\"data row21 col6\" >0.945556</td>\n",
       "      <td id=\"T_70445_row21_col7\" class=\"data row21 col7\" >0.863737</td>\n",
       "      <td id=\"T_70445_row21_col8\" class=\"data row21 col8\" >0.984000</td>\n",
       "      <td id=\"T_70445_row21_col9\" class=\"data row21 col9\" >0.618617</td>\n",
       "      <td id=\"T_70445_row21_col10\" class=\"data row21 col10\" >0.672846</td>\n",
       "      <td id=\"T_70445_row21_col11\" class=\"data row21 col11\" >79.514538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
       "      <td id=\"T_70445_row22_col0\" class=\"data row22 col0\" >103961856</td>\n",
       "      <td id=\"T_70445_row22_col1\" class=\"data row22 col1\" >8</td>\n",
       "      <td id=\"T_70445_row22_col2\" class=\"data row22 col2\" >8</td>\n",
       "      <td id=\"T_70445_row22_col3\" class=\"data row22 col3\" >0.924324</td>\n",
       "      <td id=\"T_70445_row22_col4\" class=\"data row22 col4\" >0.674667</td>\n",
       "      <td id=\"T_70445_row22_col5\" class=\"data row22 col5\" >0.824127</td>\n",
       "      <td id=\"T_70445_row22_col6\" class=\"data row22 col6\" >0.968518</td>\n",
       "      <td id=\"T_70445_row22_col7\" class=\"data row22 col7\" >0.931829</td>\n",
       "      <td id=\"T_70445_row22_col8\" class=\"data row22 col8\" >0.991500</td>\n",
       "      <td id=\"T_70445_row22_col9\" class=\"data row22 col9\" >0.690426</td>\n",
       "      <td id=\"T_70445_row22_col10\" class=\"data row22 col10\" >0.684685</td>\n",
       "      <td id=\"T_70445_row22_col11\" class=\"data row22 col11\" >83.625954</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
       "      <td id=\"T_70445_row23_col0\" class=\"data row23 col0\" >114578688</td>\n",
       "      <td id=\"T_70445_row23_col1\" class=\"data row23 col1\" >8</td>\n",
       "      <td id=\"T_70445_row23_col2\" class=\"data row23 col2\" >16</td>\n",
       "      <td id=\"T_70445_row23_col3\" class=\"data row23 col3\" >0.944683</td>\n",
       "      <td id=\"T_70445_row23_col4\" class=\"data row23 col4\" >0.708867</td>\n",
       "      <td id=\"T_70445_row23_col5\" class=\"data row23 col5\" >0.869841</td>\n",
       "      <td id=\"T_70445_row23_col6\" class=\"data row23 col6\" >0.980370</td>\n",
       "      <td id=\"T_70445_row23_col7\" class=\"data row23 col7\" >0.959382</td>\n",
       "      <td id=\"T_70445_row23_col8\" class=\"data row23 col8\" >0.994700</td>\n",
       "      <td id=\"T_70445_row23_col9\" class=\"data row23 col9\" >0.733511</td>\n",
       "      <td id=\"T_70445_row23_col10\" class=\"data row23 col10\" >0.698841</td>\n",
       "      <td id=\"T_70445_row23_col11\" class=\"data row23 col11\" >86.127457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
       "      <td id=\"T_70445_row24_col0\" class=\"data row24 col0\" >135812352</td>\n",
       "      <td id=\"T_70445_row24_col1\" class=\"data row24 col1\" >8</td>\n",
       "      <td id=\"T_70445_row24_col2\" class=\"data row24 col2\" >32</td>\n",
       "      <td id=\"T_70445_row24_col3\" class=\"data row24 col3\" >0.953404</td>\n",
       "      <td id=\"T_70445_row24_col4\" class=\"data row24 col4\" >0.743813</td>\n",
       "      <td id=\"T_70445_row24_col5\" class=\"data row24 col5\" >0.894921</td>\n",
       "      <td id=\"T_70445_row24_col6\" class=\"data row24 col6\" >0.981111</td>\n",
       "      <td id=\"T_70445_row24_col7\" class=\"data row24 col7\" >0.972763</td>\n",
       "      <td id=\"T_70445_row24_col8\" class=\"data row24 col8\" >0.994900</td>\n",
       "      <td id=\"T_70445_row24_col9\" class=\"data row24 col9\" >0.762766</td>\n",
       "      <td id=\"T_70445_row24_col10\" class=\"data row24 col10\" >0.713552</td>\n",
       "      <td id=\"T_70445_row24_col11\" class=\"data row24 col11\" >87.715364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
       "      <td id=\"T_70445_row25_col0\" class=\"data row25 col0\" >178279680</td>\n",
       "      <td id=\"T_70445_row25_col1\" class=\"data row25 col1\" >8</td>\n",
       "      <td id=\"T_70445_row25_col2\" class=\"data row25 col2\" >64</td>\n",
       "      <td id=\"T_70445_row25_col3\" class=\"data row25 col3\" >0.956092</td>\n",
       "      <td id=\"T_70445_row25_col4\" class=\"data row25 col4\" >0.763462</td>\n",
       "      <td id=\"T_70445_row25_col5\" class=\"data row25 col5\" >0.905079</td>\n",
       "      <td id=\"T_70445_row25_col6\" class=\"data row25 col6\" >0.981111</td>\n",
       "      <td id=\"T_70445_row25_col7\" class=\"data row25 col7\" >0.978226</td>\n",
       "      <td id=\"T_70445_row25_col8\" class=\"data row25 col8\" >0.995400</td>\n",
       "      <td id=\"T_70445_row25_col9\" class=\"data row25 col9\" >0.775000</td>\n",
       "      <td id=\"T_70445_row25_col10\" class=\"data row25 col10\" >0.727053</td>\n",
       "      <td id=\"T_70445_row25_col11\" class=\"data row25 col11\" >88.517806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
       "      <td id=\"T_70445_row26_col0\" class=\"data row26 col0\" >263214336</td>\n",
       "      <td id=\"T_70445_row26_col1\" class=\"data row26 col1\" >8</td>\n",
       "      <td id=\"T_70445_row26_col2\" class=\"data row26 col2\" >128</td>\n",
       "      <td id=\"T_70445_row26_col3\" class=\"data row26 col3\" >0.957591</td>\n",
       "      <td id=\"T_70445_row26_col4\" class=\"data row26 col4\" >0.777391</td>\n",
       "      <td id=\"T_70445_row26_col5\" class=\"data row26 col5\" >0.910635</td>\n",
       "      <td id=\"T_70445_row26_col6\" class=\"data row26 col6\" >0.980741</td>\n",
       "      <td id=\"T_70445_row26_col7\" class=\"data row26 col7\" >0.981156</td>\n",
       "      <td id=\"T_70445_row26_col8\" class=\"data row26 col8\" >0.995700</td>\n",
       "      <td id=\"T_70445_row26_col9\" class=\"data row26 col9\" >0.782447</td>\n",
       "      <td id=\"T_70445_row26_col10\" class=\"data row26 col10\" >0.736171</td>\n",
       "      <td id=\"T_70445_row26_col11\" class=\"data row26 col11\" >89.022891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
       "      <td id=\"T_70445_row27_col0\" class=\"data row27 col0\" >772822272</td>\n",
       "      <td id=\"T_70445_row27_col1\" class=\"data row27 col1\" >8</td>\n",
       "      <td id=\"T_70445_row27_col2\" class=\"data row27 col2\" >-1</td>\n",
       "      <td id=\"T_70445_row27_col3\" class=\"data row27 col3\" >0.957936</td>\n",
       "      <td id=\"T_70445_row27_col4\" class=\"data row27 col4\" >0.787962</td>\n",
       "      <td id=\"T_70445_row27_col5\" class=\"data row27 col5\" >0.913333</td>\n",
       "      <td id=\"T_70445_row27_col6\" class=\"data row27 col6\" >0.981111</td>\n",
       "      <td id=\"T_70445_row27_col7\" class=\"data row27 col7\" >0.981948</td>\n",
       "      <td id=\"T_70445_row27_col8\" class=\"data row27 col8\" >0.995700</td>\n",
       "      <td id=\"T_70445_row27_col9\" class=\"data row27 col9\" >0.786170</td>\n",
       "      <td id=\"T_70445_row27_col10\" class=\"data row27 col10\" >0.743577</td>\n",
       "      <td id=\"T_70445_row27_col11\" class=\"data row27 col11\" >89.346717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
       "      <td id=\"T_70445_row28_col0\" class=\"data row28 col0\" >103961856</td>\n",
       "      <td id=\"T_70445_row28_col1\" class=\"data row28 col1\" >16</td>\n",
       "      <td id=\"T_70445_row28_col2\" class=\"data row28 col2\" >4</td>\n",
       "      <td id=\"T_70445_row28_col3\" class=\"data row28 col3\" >0.907537</td>\n",
       "      <td id=\"T_70445_row28_col4\" class=\"data row28 col4\" >0.642706</td>\n",
       "      <td id=\"T_70445_row28_col5\" class=\"data row28 col5\" >0.774127</td>\n",
       "      <td id=\"T_70445_row28_col6\" class=\"data row28 col6\" >0.943704</td>\n",
       "      <td id=\"T_70445_row28_col7\" class=\"data row28 col7\" >0.866904</td>\n",
       "      <td id=\"T_70445_row28_col8\" class=\"data row28 col8\" >0.985000</td>\n",
       "      <td id=\"T_70445_row28_col9\" class=\"data row28 col9\" >0.626064</td>\n",
       "      <td id=\"T_70445_row28_col10\" class=\"data row28 col10\" >0.674358</td>\n",
       "      <td id=\"T_70445_row28_col11\" class=\"data row28 col11\" >80.254994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
       "      <td id=\"T_70445_row29_col0\" class=\"data row29 col0\" >109270272</td>\n",
       "      <td id=\"T_70445_row29_col1\" class=\"data row29 col1\" >16</td>\n",
       "      <td id=\"T_70445_row29_col2\" class=\"data row29 col2\" >8</td>\n",
       "      <td id=\"T_70445_row29_col3\" class=\"data row29 col3\" >0.946412</td>\n",
       "      <td id=\"T_70445_row29_col4\" class=\"data row29 col4\" >0.673299</td>\n",
       "      <td id=\"T_70445_row29_col5\" class=\"data row29 col5\" >0.831429</td>\n",
       "      <td id=\"T_70445_row29_col6\" class=\"data row29 col6\" >0.971482</td>\n",
       "      <td id=\"T_70445_row29_col7\" class=\"data row29 col7\" >0.933967</td>\n",
       "      <td id=\"T_70445_row29_col8\" class=\"data row29 col8\" >0.991800</td>\n",
       "      <td id=\"T_70445_row29_col9\" class=\"data row29 col9\" >0.688830</td>\n",
       "      <td id=\"T_70445_row29_col10\" class=\"data row29 col10\" >0.685542</td>\n",
       "      <td id=\"T_70445_row29_col11\" class=\"data row29 col11\" >84.034495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row30\" class=\"row_heading level0 row30\" >30</th>\n",
       "      <td id=\"T_70445_row30_col0\" class=\"data row30 col0\" >119887104</td>\n",
       "      <td id=\"T_70445_row30_col1\" class=\"data row30 col1\" >16</td>\n",
       "      <td id=\"T_70445_row30_col2\" class=\"data row30 col2\" >16</td>\n",
       "      <td id=\"T_70445_row30_col3\" class=\"data row30 col3\" >0.960356</td>\n",
       "      <td id=\"T_70445_row30_col4\" class=\"data row30 col4\" >0.713095</td>\n",
       "      <td id=\"T_70445_row30_col5\" class=\"data row30 col5\" >0.882698</td>\n",
       "      <td id=\"T_70445_row30_col6\" class=\"data row30 col6\" >0.981111</td>\n",
       "      <td id=\"T_70445_row30_col7\" class=\"data row30 col7\" >0.960016</td>\n",
       "      <td id=\"T_70445_row30_col8\" class=\"data row30 col8\" >0.994900</td>\n",
       "      <td id=\"T_70445_row30_col9\" class=\"data row30 col9\" >0.735638</td>\n",
       "      <td id=\"T_70445_row30_col10\" class=\"data row30 col10\" >0.700957</td>\n",
       "      <td id=\"T_70445_row30_col11\" class=\"data row30 col11\" >86.609659</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row31\" class=\"row_heading level0 row31\" >31</th>\n",
       "      <td id=\"T_70445_row31_col0\" class=\"data row31 col0\" >141120768</td>\n",
       "      <td id=\"T_70445_row31_col1\" class=\"data row31 col1\" >16</td>\n",
       "      <td id=\"T_70445_row31_col2\" class=\"data row31 col2\" >32</td>\n",
       "      <td id=\"T_70445_row31_col3\" class=\"data row31 col3\" >0.966157</td>\n",
       "      <td id=\"T_70445_row31_col4\" class=\"data row31 col4\" >0.748290</td>\n",
       "      <td id=\"T_70445_row31_col5\" class=\"data row31 col5\" >0.906508</td>\n",
       "      <td id=\"T_70445_row31_col6\" class=\"data row31 col6\" >0.983333</td>\n",
       "      <td id=\"T_70445_row31_col7\" class=\"data row31 col7\" >0.971180</td>\n",
       "      <td id=\"T_70445_row31_col8\" class=\"data row31 col8\" >0.995400</td>\n",
       "      <td id=\"T_70445_row31_col9\" class=\"data row31 col9\" >0.768085</td>\n",
       "      <td id=\"T_70445_row31_col10\" class=\"data row31 col10\" >0.715667</td>\n",
       "      <td id=\"T_70445_row31_col11\" class=\"data row31 col11\" >88.182758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row32\" class=\"row_heading level0 row32\" >32</th>\n",
       "      <td id=\"T_70445_row32_col0\" class=\"data row32 col0\" >183588096</td>\n",
       "      <td id=\"T_70445_row32_col1\" class=\"data row32 col1\" >16</td>\n",
       "      <td id=\"T_70445_row32_col2\" class=\"data row32 col2\" >64</td>\n",
       "      <td id=\"T_70445_row32_col3\" class=\"data row32 col3\" >0.967540</td>\n",
       "      <td id=\"T_70445_row32_col4\" class=\"data row32 col4\" >0.766198</td>\n",
       "      <td id=\"T_70445_row32_col5\" class=\"data row32 col5\" >0.915238</td>\n",
       "      <td id=\"T_70445_row32_col6\" class=\"data row32 col6\" >0.984074</td>\n",
       "      <td id=\"T_70445_row32_col7\" class=\"data row32 col7\" >0.977276</td>\n",
       "      <td id=\"T_70445_row32_col8\" class=\"data row32 col8\" >0.995900</td>\n",
       "      <td id=\"T_70445_row32_col9\" class=\"data row32 col9\" >0.775532</td>\n",
       "      <td id=\"T_70445_row32_col10\" class=\"data row32 col10\" >0.727657</td>\n",
       "      <td id=\"T_70445_row32_col11\" class=\"data row32 col11\" >88.867699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row33\" class=\"row_heading level0 row33\" >33</th>\n",
       "      <td id=\"T_70445_row33_col0\" class=\"data row33 col0\" >268522752</td>\n",
       "      <td id=\"T_70445_row33_col1\" class=\"data row33 col1\" >16</td>\n",
       "      <td id=\"T_70445_row33_col2\" class=\"data row33 col2\" >128</td>\n",
       "      <td id=\"T_70445_row33_col3\" class=\"data row33 col3\" >0.968270</td>\n",
       "      <td id=\"T_70445_row33_col4\" class=\"data row33 col4\" >0.778386</td>\n",
       "      <td id=\"T_70445_row33_col5\" class=\"data row33 col5\" >0.919841</td>\n",
       "      <td id=\"T_70445_row33_col6\" class=\"data row33 col6\" >0.983333</td>\n",
       "      <td id=\"T_70445_row33_col7\" class=\"data row33 col7\" >0.980760</td>\n",
       "      <td id=\"T_70445_row33_col8\" class=\"data row33 col8\" >0.996100</td>\n",
       "      <td id=\"T_70445_row33_col9\" class=\"data row33 col9\" >0.781383</td>\n",
       "      <td id=\"T_70445_row33_col10\" class=\"data row33 col10\" >0.736071</td>\n",
       "      <td id=\"T_70445_row33_col11\" class=\"data row33 col11\" >89.301798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row34\" class=\"row_heading level0 row34\" >34</th>\n",
       "      <td id=\"T_70445_row34_col0\" class=\"data row34 col0\" >778130688</td>\n",
       "      <td id=\"T_70445_row34_col1\" class=\"data row34 col1\" >16</td>\n",
       "      <td id=\"T_70445_row34_col2\" class=\"data row34 col2\" >-1</td>\n",
       "      <td id=\"T_70445_row34_col3\" class=\"data row34 col3\" >0.968462</td>\n",
       "      <td id=\"T_70445_row34_col4\" class=\"data row34 col4\" >0.786967</td>\n",
       "      <td id=\"T_70445_row34_col5\" class=\"data row34 col5\" >0.922857</td>\n",
       "      <td id=\"T_70445_row34_col6\" class=\"data row34 col6\" >0.983704</td>\n",
       "      <td id=\"T_70445_row34_col7\" class=\"data row34 col7\" >0.981789</td>\n",
       "      <td id=\"T_70445_row34_col8\" class=\"data row34 col8\" >0.996200</td>\n",
       "      <td id=\"T_70445_row34_col9\" class=\"data row34 col9\" >0.786170</td>\n",
       "      <td id=\"T_70445_row34_col10\" class=\"data row34 col10\" >0.742922</td>\n",
       "      <td id=\"T_70445_row34_col11\" class=\"data row34 col11\" >89.613388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row35\" class=\"row_heading level0 row35\" >35</th>\n",
       "      <td id=\"T_70445_row35_col0\" class=\"data row35 col0\" >114578688</td>\n",
       "      <td id=\"T_70445_row35_col1\" class=\"data row35 col1\" >32</td>\n",
       "      <td id=\"T_70445_row35_col2\" class=\"data row35 col2\" >4</td>\n",
       "      <td id=\"T_70445_row35_col3\" class=\"data row35 col3\" >0.921097</td>\n",
       "      <td id=\"T_70445_row35_col4\" class=\"data row35 col4\" >0.638975</td>\n",
       "      <td id=\"T_70445_row35_col5\" class=\"data row35 col5\" >0.782540</td>\n",
       "      <td id=\"T_70445_row35_col6\" class=\"data row35 col6\" >0.937407</td>\n",
       "      <td id=\"T_70445_row35_col7\" class=\"data row35 col7\" >0.872288</td>\n",
       "      <td id=\"T_70445_row35_col8\" class=\"data row35 col8\" >0.984900</td>\n",
       "      <td id=\"T_70445_row35_col9\" class=\"data row35 col9\" >0.628723</td>\n",
       "      <td id=\"T_70445_row35_col10\" class=\"data row35 col10\" >0.672292</td>\n",
       "      <td id=\"T_70445_row35_col11\" class=\"data row35 col11\" >80.477791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row36\" class=\"row_heading level0 row36\" >36</th>\n",
       "      <td id=\"T_70445_row36_col0\" class=\"data row36 col0\" >119887104</td>\n",
       "      <td id=\"T_70445_row36_col1\" class=\"data row36 col1\" >32</td>\n",
       "      <td id=\"T_70445_row36_col2\" class=\"data row36 col2\" >8</td>\n",
       "      <td id=\"T_70445_row36_col3\" class=\"data row36 col3\" >0.953480</td>\n",
       "      <td id=\"T_70445_row36_col4\" class=\"data row36 col4\" >0.671807</td>\n",
       "      <td id=\"T_70445_row36_col5\" class=\"data row36 col5\" >0.837778</td>\n",
       "      <td id=\"T_70445_row36_col6\" class=\"data row36 col6\" >0.970741</td>\n",
       "      <td id=\"T_70445_row36_col7\" class=\"data row36 col7\" >0.934996</td>\n",
       "      <td id=\"T_70445_row36_col8\" class=\"data row36 col8\" >0.992100</td>\n",
       "      <td id=\"T_70445_row36_col9\" class=\"data row36 col9\" >0.689362</td>\n",
       "      <td id=\"T_70445_row36_col10\" class=\"data row36 col10\" >0.684282</td>\n",
       "      <td id=\"T_70445_row36_col11\" class=\"data row36 col11\" >84.181821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row37\" class=\"row_heading level0 row37\" >37</th>\n",
       "      <td id=\"T_70445_row37_col0\" class=\"data row37 col0\" >130503936</td>\n",
       "      <td id=\"T_70445_row37_col1\" class=\"data row37 col1\" >32</td>\n",
       "      <td id=\"T_70445_row37_col2\" class=\"data row37 col2\" >16</td>\n",
       "      <td id=\"T_70445_row37_col3\" class=\"data row37 col3\" >0.964505</td>\n",
       "      <td id=\"T_70445_row37_col4\" class=\"data row37 col4\" >0.713220</td>\n",
       "      <td id=\"T_70445_row37_col5\" class=\"data row37 col5\" >0.889048</td>\n",
       "      <td id=\"T_70445_row37_col6\" class=\"data row37 col6\" >0.981481</td>\n",
       "      <td id=\"T_70445_row37_col7\" class=\"data row37 col7\" >0.960649</td>\n",
       "      <td id=\"T_70445_row37_col8\" class=\"data row37 col8\" >0.995000</td>\n",
       "      <td id=\"T_70445_row37_col9\" class=\"data row37 col9\" >0.729787</td>\n",
       "      <td id=\"T_70445_row37_col10\" class=\"data row37 col10\" >0.698489</td>\n",
       "      <td id=\"T_70445_row37_col11\" class=\"data row37 col11\" >86.652240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row38\" class=\"row_heading level0 row38\" >38</th>\n",
       "      <td id=\"T_70445_row38_col0\" class=\"data row38 col0\" >151737600</td>\n",
       "      <td id=\"T_70445_row38_col1\" class=\"data row38 col1\" >32</td>\n",
       "      <td id=\"T_70445_row38_col2\" class=\"data row38 col2\" >32</td>\n",
       "      <td id=\"T_70445_row38_col3\" class=\"data row38 col3\" >0.968692</td>\n",
       "      <td id=\"T_70445_row38_col4\" class=\"data row38 col4\" >0.745927</td>\n",
       "      <td id=\"T_70445_row38_col5\" class=\"data row38 col5\" >0.912381</td>\n",
       "      <td id=\"T_70445_row38_col6\" class=\"data row38 col6\" >0.981481</td>\n",
       "      <td id=\"T_70445_row38_col7\" class=\"data row38 col7\" >0.973951</td>\n",
       "      <td id=\"T_70445_row38_col8\" class=\"data row38 col8\" >0.995700</td>\n",
       "      <td id=\"T_70445_row38_col9\" class=\"data row38 col9\" >0.756915</td>\n",
       "      <td id=\"T_70445_row38_col10\" class=\"data row38 col10\" >0.716423</td>\n",
       "      <td id=\"T_70445_row38_col11\" class=\"data row38 col11\" >88.143386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row39\" class=\"row_heading level0 row39\" >39</th>\n",
       "      <td id=\"T_70445_row39_col0\" class=\"data row39 col0\" >194204928</td>\n",
       "      <td id=\"T_70445_row39_col1\" class=\"data row39 col1\" >32</td>\n",
       "      <td id=\"T_70445_row39_col2\" class=\"data row39 col2\" >64</td>\n",
       "      <td id=\"T_70445_row39_col3\" class=\"data row39 col3\" >0.969883</td>\n",
       "      <td id=\"T_70445_row39_col4\" class=\"data row39 col4\" >0.765576</td>\n",
       "      <td id=\"T_70445_row39_col5\" class=\"data row39 col5\" >0.920794</td>\n",
       "      <td id=\"T_70445_row39_col6\" class=\"data row39 col6\" >0.980741</td>\n",
       "      <td id=\"T_70445_row39_col7\" class=\"data row39 col7\" >0.979731</td>\n",
       "      <td id=\"T_70445_row39_col8\" class=\"data row39 col8\" >0.996300</td>\n",
       "      <td id=\"T_70445_row39_col9\" class=\"data row39 col9\" >0.774468</td>\n",
       "      <td id=\"T_70445_row39_col10\" class=\"data row39 col10\" >0.729370</td>\n",
       "      <td id=\"T_70445_row39_col11\" class=\"data row39 col11\" >88.960789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row40\" class=\"row_heading level0 row40\" >40</th>\n",
       "      <td id=\"T_70445_row40_col0\" class=\"data row40 col0\" >279139584</td>\n",
       "      <td id=\"T_70445_row40_col1\" class=\"data row40 col1\" >32</td>\n",
       "      <td id=\"T_70445_row40_col2\" class=\"data row40 col2\" >128</td>\n",
       "      <td id=\"T_70445_row40_col3\" class=\"data row40 col3\" >0.970152</td>\n",
       "      <td id=\"T_70445_row40_col4\" class=\"data row40 col4\" >0.775277</td>\n",
       "      <td id=\"T_70445_row40_col5\" class=\"data row40 col5\" >0.925873</td>\n",
       "      <td id=\"T_70445_row40_col6\" class=\"data row40 col6\" >0.981481</td>\n",
       "      <td id=\"T_70445_row40_col7\" class=\"data row40 col7\" >0.981473</td>\n",
       "      <td id=\"T_70445_row40_col8\" class=\"data row40 col8\" >0.996300</td>\n",
       "      <td id=\"T_70445_row40_col9\" class=\"data row40 col9\" >0.781915</td>\n",
       "      <td id=\"T_70445_row40_col10\" class=\"data row40 col10\" >0.737179</td>\n",
       "      <td id=\"T_70445_row40_col11\" class=\"data row40 col11\" >89.370622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row41\" class=\"row_heading level0 row41\" >41</th>\n",
       "      <td id=\"T_70445_row41_col0\" class=\"data row41 col0\" >788747520</td>\n",
       "      <td id=\"T_70445_row41_col1\" class=\"data row41 col1\" >32</td>\n",
       "      <td id=\"T_70445_row41_col2\" class=\"data row41 col2\" >-1</td>\n",
       "      <td id=\"T_70445_row41_col3\" class=\"data row41 col3\" >0.970459</td>\n",
       "      <td id=\"T_70445_row41_col4\" class=\"data row41 col4\" >0.785972</td>\n",
       "      <td id=\"T_70445_row41_col5\" class=\"data row41 col5\" >0.928889</td>\n",
       "      <td id=\"T_70445_row41_col6\" class=\"data row41 col6\" >0.982593</td>\n",
       "      <td id=\"T_70445_row41_col7\" class=\"data row41 col7\" >0.982344</td>\n",
       "      <td id=\"T_70445_row41_col8\" class=\"data row41 col8\" >0.996200</td>\n",
       "      <td id=\"T_70445_row41_col9\" class=\"data row41 col9\" >0.781915</td>\n",
       "      <td id=\"T_70445_row41_col10\" class=\"data row41 col10\" >0.741411</td>\n",
       "      <td id=\"T_70445_row41_col11\" class=\"data row41 col11\" >89.622274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row42\" class=\"row_heading level0 row42\" >42</th>\n",
       "      <td id=\"T_70445_row42_col0\" class=\"data row42 col0\" >135812352</td>\n",
       "      <td id=\"T_70445_row42_col1\" class=\"data row42 col1\" >64</td>\n",
       "      <td id=\"T_70445_row42_col2\" class=\"data row42 col2\" >4</td>\n",
       "      <td id=\"T_70445_row42_col3\" class=\"data row42 col3\" >0.926014</td>\n",
       "      <td id=\"T_70445_row42_col4\" class=\"data row42 col4\" >0.639224</td>\n",
       "      <td id=\"T_70445_row42_col5\" class=\"data row42 col5\" >0.791111</td>\n",
       "      <td id=\"T_70445_row42_col6\" class=\"data row42 col6\" >0.930741</td>\n",
       "      <td id=\"T_70445_row42_col7\" class=\"data row42 col7\" >0.878464</td>\n",
       "      <td id=\"T_70445_row42_col8\" class=\"data row42 col8\" >0.984900</td>\n",
       "      <td id=\"T_70445_row42_col9\" class=\"data row42 col9\" >0.621809</td>\n",
       "      <td id=\"T_70445_row42_col10\" class=\"data row42 col10\" >0.671990</td>\n",
       "      <td id=\"T_70445_row42_col11\" class=\"data row42 col11\" >80.553155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row43\" class=\"row_heading level0 row43\" >43</th>\n",
       "      <td id=\"T_70445_row43_col0\" class=\"data row43 col0\" >141120768</td>\n",
       "      <td id=\"T_70445_row43_col1\" class=\"data row43 col1\" >64</td>\n",
       "      <td id=\"T_70445_row43_col2\" class=\"data row43 col2\" >8</td>\n",
       "      <td id=\"T_70445_row43_col3\" class=\"data row43 col3\" >0.956630</td>\n",
       "      <td id=\"T_70445_row43_col4\" class=\"data row43 col4\" >0.670563</td>\n",
       "      <td id=\"T_70445_row43_col5\" class=\"data row43 col5\" >0.850000</td>\n",
       "      <td id=\"T_70445_row43_col6\" class=\"data row43 col6\" >0.970741</td>\n",
       "      <td id=\"T_70445_row43_col7\" class=\"data row43 col7\" >0.938638</td>\n",
       "      <td id=\"T_70445_row43_col8\" class=\"data row43 col8\" >0.992300</td>\n",
       "      <td id=\"T_70445_row43_col9\" class=\"data row43 col9\" >0.684043</td>\n",
       "      <td id=\"T_70445_row43_col10\" class=\"data row43 col10\" >0.683123</td>\n",
       "      <td id=\"T_70445_row43_col11\" class=\"data row43 col11\" >84.325481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row44\" class=\"row_heading level0 row44\" >44</th>\n",
       "      <td id=\"T_70445_row44_col0\" class=\"data row44 col0\" >151737600</td>\n",
       "      <td id=\"T_70445_row44_col1\" class=\"data row44 col1\" >64</td>\n",
       "      <td id=\"T_70445_row44_col2\" class=\"data row44 col2\" >16</td>\n",
       "      <td id=\"T_70445_row44_col3\" class=\"data row44 col3\" >0.966080</td>\n",
       "      <td id=\"T_70445_row44_col4\" class=\"data row44 col4\" >0.711230</td>\n",
       "      <td id=\"T_70445_row44_col5\" class=\"data row44 col5\" >0.901429</td>\n",
       "      <td id=\"T_70445_row44_col6\" class=\"data row44 col6\" >0.981481</td>\n",
       "      <td id=\"T_70445_row44_col7\" class=\"data row44 col7\" >0.965400</td>\n",
       "      <td id=\"T_70445_row44_col8\" class=\"data row44 col8\" >0.994800</td>\n",
       "      <td id=\"T_70445_row44_col9\" class=\"data row44 col9\" >0.732447</td>\n",
       "      <td id=\"T_70445_row44_col10\" class=\"data row44 col10\" >0.698791</td>\n",
       "      <td id=\"T_70445_row44_col11\" class=\"data row44 col11\" >86.895721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row45\" class=\"row_heading level0 row45\" >45</th>\n",
       "      <td id=\"T_70445_row45_col0\" class=\"data row45 col0\" >172971264</td>\n",
       "      <td id=\"T_70445_row45_col1\" class=\"data row45 col1\" >64</td>\n",
       "      <td id=\"T_70445_row45_col2\" class=\"data row45 col2\" >32</td>\n",
       "      <td id=\"T_70445_row45_col3\" class=\"data row45 col3\" >0.969614</td>\n",
       "      <td id=\"T_70445_row45_col4\" class=\"data row45 col4\" >0.745678</td>\n",
       "      <td id=\"T_70445_row45_col5\" class=\"data row45 col5\" >0.925714</td>\n",
       "      <td id=\"T_70445_row45_col6\" class=\"data row45 col6\" >0.983333</td>\n",
       "      <td id=\"T_70445_row45_col7\" class=\"data row45 col7\" >0.976643</td>\n",
       "      <td id=\"T_70445_row45_col8\" class=\"data row45 col8\" >0.995500</td>\n",
       "      <td id=\"T_70445_row45_col9\" class=\"data row45 col9\" >0.763830</td>\n",
       "      <td id=\"T_70445_row45_col10\" class=\"data row45 col10\" >0.717582</td>\n",
       "      <td id=\"T_70445_row45_col11\" class=\"data row45 col11\" >88.473687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row46\" class=\"row_heading level0 row46\" >46</th>\n",
       "      <td id=\"T_70445_row46_col0\" class=\"data row46 col0\" >215438592</td>\n",
       "      <td id=\"T_70445_row46_col1\" class=\"data row46 col1\" >64</td>\n",
       "      <td id=\"T_70445_row46_col2\" class=\"data row46 col2\" >64</td>\n",
       "      <td id=\"T_70445_row46_col3\" class=\"data row46 col3\" >0.970959</td>\n",
       "      <td id=\"T_70445_row46_col4\" class=\"data row46 col4\" >0.763960</td>\n",
       "      <td id=\"T_70445_row46_col5\" class=\"data row46 col5\" >0.931111</td>\n",
       "      <td id=\"T_70445_row46_col6\" class=\"data row46 col6\" >0.983704</td>\n",
       "      <td id=\"T_70445_row46_col7\" class=\"data row46 col7\" >0.982423</td>\n",
       "      <td id=\"T_70445_row46_col8\" class=\"data row46 col8\" >0.996000</td>\n",
       "      <td id=\"T_70445_row46_col9\" class=\"data row46 col9\" >0.771277</td>\n",
       "      <td id=\"T_70445_row46_col10\" class=\"data row46 col10\" >0.729421</td>\n",
       "      <td id=\"T_70445_row46_col11\" class=\"data row46 col11\" >89.110668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row47\" class=\"row_heading level0 row47\" >47</th>\n",
       "      <td id=\"T_70445_row47_col0\" class=\"data row47 col0\" >300373248</td>\n",
       "      <td id=\"T_70445_row47_col1\" class=\"data row47 col1\" >64</td>\n",
       "      <td id=\"T_70445_row47_col2\" class=\"data row47 col2\" >128</td>\n",
       "      <td id=\"T_70445_row47_col3\" class=\"data row47 col3\" >0.971266</td>\n",
       "      <td id=\"T_70445_row47_col4\" class=\"data row47 col4\" >0.777018</td>\n",
       "      <td id=\"T_70445_row47_col5\" class=\"data row47 col5\" >0.934921</td>\n",
       "      <td id=\"T_70445_row47_col6\" class=\"data row47 col6\" >0.984444</td>\n",
       "      <td id=\"T_70445_row47_col7\" class=\"data row47 col7\" >0.984086</td>\n",
       "      <td id=\"T_70445_row47_col8\" class=\"data row47 col8\" >0.996000</td>\n",
       "      <td id=\"T_70445_row47_col9\" class=\"data row47 col9\" >0.778723</td>\n",
       "      <td id=\"T_70445_row47_col10\" class=\"data row47 col10\" >0.737481</td>\n",
       "      <td id=\"T_70445_row47_col11\" class=\"data row47 col11\" >89.549237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row48\" class=\"row_heading level0 row48\" >48</th>\n",
       "      <td id=\"T_70445_row48_col0\" class=\"data row48 col0\" >809981184</td>\n",
       "      <td id=\"T_70445_row48_col1\" class=\"data row48 col1\" >64</td>\n",
       "      <td id=\"T_70445_row48_col2\" class=\"data row48 col2\" >-1</td>\n",
       "      <td id=\"T_70445_row48_col3\" class=\"data row48 col3\" >0.971420</td>\n",
       "      <td id=\"T_70445_row48_col4\" class=\"data row48 col4\" >0.785474</td>\n",
       "      <td id=\"T_70445_row48_col5\" class=\"data row48 col5\" >0.938254</td>\n",
       "      <td id=\"T_70445_row48_col6\" class=\"data row48 col6\" >0.984444</td>\n",
       "      <td id=\"T_70445_row48_col7\" class=\"data row48 col7\" >0.984798</td>\n",
       "      <td id=\"T_70445_row48_col8\" class=\"data row48 col8\" >0.996000</td>\n",
       "      <td id=\"T_70445_row48_col9\" class=\"data row48 col9\" >0.779787</td>\n",
       "      <td id=\"T_70445_row48_col10\" class=\"data row48 col10\" >0.743627</td>\n",
       "      <td id=\"T_70445_row48_col11\" class=\"data row48 col11\" >89.797564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row49\" class=\"row_heading level0 row49\" >49</th>\n",
       "      <td id=\"T_70445_row49_col0\" class=\"data row49 col0\" >178279680</td>\n",
       "      <td id=\"T_70445_row49_col1\" class=\"data row49 col1\" >128</td>\n",
       "      <td id=\"T_70445_row49_col2\" class=\"data row49 col2\" >4</td>\n",
       "      <td id=\"T_70445_row49_col3\" class=\"data row49 col3\" >0.927013</td>\n",
       "      <td id=\"T_70445_row49_col4\" class=\"data row49 col4\" >0.635866</td>\n",
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       "      <td id=\"T_70445_row49_col7\" class=\"data row49 col7\" >0.880443</td>\n",
       "      <td id=\"T_70445_row49_col8\" class=\"data row49 col8\" >0.984800</td>\n",
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       "    <tr>\n",
       "      <th id=\"T_70445_level0_row50\" class=\"row_heading level0 row50\" >50</th>\n",
       "      <td id=\"T_70445_row50_col0\" class=\"data row50 col0\" >183588096</td>\n",
       "      <td id=\"T_70445_row50_col1\" class=\"data row50 col1\" >128</td>\n",
       "      <td id=\"T_70445_row50_col2\" class=\"data row50 col2\" >8</td>\n",
       "      <td id=\"T_70445_row50_col3\" class=\"data row50 col3\" >0.956976</td>\n",
       "      <td id=\"T_70445_row50_col4\" class=\"data row50 col4\" >0.668947</td>\n",
       "      <td id=\"T_70445_row50_col5\" class=\"data row50 col5\" >0.858095</td>\n",
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       "      <td id=\"T_70445_row50_col7\" class=\"data row50 col7\" >0.943072</td>\n",
       "      <td id=\"T_70445_row50_col8\" class=\"data row50 col8\" >0.992800</td>\n",
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       "    <tr>\n",
       "      <th id=\"T_70445_level0_row51\" class=\"row_heading level0 row51\" >51</th>\n",
       "      <td id=\"T_70445_row51_col0\" class=\"data row51 col0\" >194204928</td>\n",
       "      <td id=\"T_70445_row51_col1\" class=\"data row51 col1\" >128</td>\n",
       "      <td id=\"T_70445_row51_col2\" class=\"data row51 col2\" >16</td>\n",
       "      <td id=\"T_70445_row51_col3\" class=\"data row51 col3\" >0.966003</td>\n",
       "      <td id=\"T_70445_row51_col4\" class=\"data row51 col4\" >0.708867</td>\n",
       "      <td id=\"T_70445_row51_col5\" class=\"data row51 col5\" >0.906508</td>\n",
       "      <td id=\"T_70445_row51_col6\" class=\"data row51 col6\" >0.978889</td>\n",
       "      <td id=\"T_70445_row51_col7\" class=\"data row51 col7\" >0.967458</td>\n",
       "      <td id=\"T_70445_row51_col8\" class=\"data row51 col8\" >0.994900</td>\n",
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       "      <td id=\"T_70445_row51_col11\" class=\"data row51 col11\" >86.947868</td>\n",
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       "    <tr>\n",
       "      <th id=\"T_70445_level0_row52\" class=\"row_heading level0 row52\" >52</th>\n",
       "      <td id=\"T_70445_row52_col0\" class=\"data row52 col0\" >215438592</td>\n",
       "      <td id=\"T_70445_row52_col1\" class=\"data row52 col1\" >128</td>\n",
       "      <td id=\"T_70445_row52_col2\" class=\"data row52 col2\" >32</td>\n",
       "      <td id=\"T_70445_row52_col3\" class=\"data row52 col3\" >0.969537</td>\n",
       "      <td id=\"T_70445_row52_col4\" class=\"data row52 col4\" >0.744684</td>\n",
       "      <td id=\"T_70445_row52_col5\" class=\"data row52 col5\" >0.932064</td>\n",
       "      <td id=\"T_70445_row52_col6\" class=\"data row52 col6\" >0.982222</td>\n",
       "      <td id=\"T_70445_row52_col7\" class=\"data row52 col7\" >0.979414</td>\n",
       "      <td id=\"T_70445_row52_col8\" class=\"data row52 col8\" >0.995400</td>\n",
       "      <td id=\"T_70445_row52_col9\" class=\"data row52 col9\" >0.758511</td>\n",
       "      <td id=\"T_70445_row52_col10\" class=\"data row52 col10\" >0.712997</td>\n",
       "      <td id=\"T_70445_row52_col11\" class=\"data row52 col11\" >88.435362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row53\" class=\"row_heading level0 row53\" >53</th>\n",
       "      <td id=\"T_70445_row53_col0\" class=\"data row53 col0\" >257905920</td>\n",
       "      <td id=\"T_70445_row53_col1\" class=\"data row53 col1\" >128</td>\n",
       "      <td id=\"T_70445_row53_col2\" class=\"data row53 col2\" >64</td>\n",
       "      <td id=\"T_70445_row53_col3\" class=\"data row53 col3\" >0.970191</td>\n",
       "      <td id=\"T_70445_row53_col4\" class=\"data row53 col4\" >0.760851</td>\n",
       "      <td id=\"T_70445_row53_col5\" class=\"data row53 col5\" >0.938571</td>\n",
       "      <td id=\"T_70445_row53_col6\" class=\"data row53 col6\" >0.984444</td>\n",
       "      <td id=\"T_70445_row53_col7\" class=\"data row53 col7\" >0.985669</td>\n",
       "      <td id=\"T_70445_row53_col8\" class=\"data row53 col8\" >0.996000</td>\n",
       "      <td id=\"T_70445_row53_col9\" class=\"data row53 col9\" >0.767021</td>\n",
       "      <td id=\"T_70445_row53_col10\" class=\"data row53 col10\" >0.725693</td>\n",
       "      <td id=\"T_70445_row53_col11\" class=\"data row53 col11\" >89.105501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row54\" class=\"row_heading level0 row54\" >54</th>\n",
       "      <td id=\"T_70445_row54_col0\" class=\"data row54 col0\" >342840576</td>\n",
       "      <td id=\"T_70445_row54_col1\" class=\"data row54 col1\" >128</td>\n",
       "      <td id=\"T_70445_row54_col2\" class=\"data row54 col2\" >128</td>\n",
       "      <td id=\"T_70445_row54_col3\" class=\"data row54 col3\" >0.970383</td>\n",
       "      <td id=\"T_70445_row54_col4\" class=\"data row54 col4\" >0.774282</td>\n",
       "      <td id=\"T_70445_row54_col5\" class=\"data row54 col5\" >0.941905</td>\n",
       "      <td id=\"T_70445_row54_col6\" class=\"data row54 col6\" >0.984444</td>\n",
       "      <td id=\"T_70445_row54_col7\" class=\"data row54 col7\" >0.988124</td>\n",
       "      <td id=\"T_70445_row54_col8\" class=\"data row54 col8\" >0.996300</td>\n",
       "      <td id=\"T_70445_row54_col9\" class=\"data row54 col9\" >0.772872</td>\n",
       "      <td id=\"T_70445_row54_col10\" class=\"data row54 col10\" >0.736222</td>\n",
       "      <td id=\"T_70445_row54_col11\" class=\"data row54 col11\" >89.556640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row55\" class=\"row_heading level0 row55\" >55</th>\n",
       "      <td id=\"T_70445_row55_col0\" class=\"data row55 col0\" >852448512</td>\n",
       "      <td id=\"T_70445_row55_col1\" class=\"data row55 col1\" >128</td>\n",
       "      <td id=\"T_70445_row55_col2\" class=\"data row55 col2\" >-1</td>\n",
       "      <td id=\"T_70445_row55_col3\" class=\"data row55 col3\" >0.970767</td>\n",
       "      <td id=\"T_70445_row55_col4\" class=\"data row55 col4\" >0.783236</td>\n",
       "      <td id=\"T_70445_row55_col5\" class=\"data row55 col5\" >0.943333</td>\n",
       "      <td id=\"T_70445_row55_col6\" class=\"data row55 col6\" >0.984074</td>\n",
       "      <td id=\"T_70445_row55_col7\" class=\"data row55 col7\" >0.988678</td>\n",
       "      <td id=\"T_70445_row55_col8\" class=\"data row55 col8\" >0.996300</td>\n",
       "      <td id=\"T_70445_row55_col9\" class=\"data row55 col9\" >0.778723</td>\n",
       "      <td id=\"T_70445_row55_col10\" class=\"data row55 col10\" >0.741259</td>\n",
       "      <td id=\"T_70445_row55_col11\" class=\"data row55 col11\" >89.829633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row56\" class=\"row_heading level0 row56\" >56</th>\n",
       "      <td id=\"T_70445_row56_col0\" class=\"data row56 col0\" >263214336</td>\n",
       "      <td id=\"T_70445_row56_col1\" class=\"data row56 col1\" >256</td>\n",
       "      <td id=\"T_70445_row56_col2\" class=\"data row56 col2\" >4</td>\n",
       "      <td id=\"T_70445_row56_col3\" class=\"data row56 col3\" >0.919484</td>\n",
       "      <td id=\"T_70445_row56_col4\" class=\"data row56 col4\" >0.639473</td>\n",
       "      <td id=\"T_70445_row56_col5\" class=\"data row56 col5\" >0.803810</td>\n",
       "      <td id=\"T_70445_row56_col6\" class=\"data row56 col6\" >0.919259</td>\n",
       "      <td id=\"T_70445_row56_col7\" class=\"data row56 col7\" >0.885115</td>\n",
       "      <td id=\"T_70445_row56_col8\" class=\"data row56 col8\" >0.984100</td>\n",
       "      <td id=\"T_70445_row56_col9\" class=\"data row56 col9\" >0.623404</td>\n",
       "      <td id=\"T_70445_row56_col10\" class=\"data row56 col10\" >0.670176</td>\n",
       "      <td id=\"T_70445_row56_col11\" class=\"data row56 col11\" >80.560257</td>\n",
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       "    <tr>\n",
       "      <th id=\"T_70445_level0_row57\" class=\"row_heading level0 row57\" >57</th>\n",
       "      <td id=\"T_70445_row57_col0\" class=\"data row57 col0\" >268522752</td>\n",
       "      <td id=\"T_70445_row57_col1\" class=\"data row57 col1\" >256</td>\n",
       "      <td id=\"T_70445_row57_col2\" class=\"data row57 col2\" >8</td>\n",
       "      <td id=\"T_70445_row57_col3\" class=\"data row57 col3\" >0.952674</td>\n",
       "      <td id=\"T_70445_row57_col4\" class=\"data row57 col4\" >0.667579</td>\n",
       "      <td id=\"T_70445_row57_col5\" class=\"data row57 col5\" >0.862063</td>\n",
       "      <td id=\"T_70445_row57_col6\" class=\"data row57 col6\" >0.964074</td>\n",
       "      <td id=\"T_70445_row57_col7\" class=\"data row57 col7\" >0.945210</td>\n",
       "      <td id=\"T_70445_row57_col8\" class=\"data row57 col8\" >0.992400</td>\n",
       "      <td id=\"T_70445_row57_col9\" class=\"data row57 col9\" >0.685638</td>\n",
       "      <td id=\"T_70445_row57_col10\" class=\"data row57 col10\" >0.680151</td>\n",
       "      <td id=\"T_70445_row57_col11\" class=\"data row57 col11\" >84.372362</td>\n",
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       "    <tr>\n",
       "      <th id=\"T_70445_level0_row58\" class=\"row_heading level0 row58\" >58</th>\n",
       "      <td id=\"T_70445_row58_col0\" class=\"data row58 col0\" >279139584</td>\n",
       "      <td id=\"T_70445_row58_col1\" class=\"data row58 col1\" >256</td>\n",
       "      <td id=\"T_70445_row58_col2\" class=\"data row58 col2\" >16</td>\n",
       "      <td id=\"T_70445_row58_col3\" class=\"data row58 col3\" >0.961432</td>\n",
       "      <td id=\"T_70445_row58_col4\" class=\"data row58 col4\" >0.707748</td>\n",
       "      <td id=\"T_70445_row58_col5\" class=\"data row58 col5\" >0.909365</td>\n",
       "      <td id=\"T_70445_row58_col6\" class=\"data row58 col6\" >0.977778</td>\n",
       "      <td id=\"T_70445_row58_col7\" class=\"data row58 col7\" >0.969121</td>\n",
       "      <td id=\"T_70445_row58_col8\" class=\"data row58 col8\" >0.994700</td>\n",
       "      <td id=\"T_70445_row58_col9\" class=\"data row58 col9\" >0.739362</td>\n",
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       "      <td id=\"T_70445_row58_col11\" class=\"data row58 col11\" >86.961704</td>\n",
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       "    <tr>\n",
       "      <th id=\"T_70445_level0_row59\" class=\"row_heading level0 row59\" >59</th>\n",
       "      <td id=\"T_70445_row59_col0\" class=\"data row59 col0\" >300373248</td>\n",
       "      <td id=\"T_70445_row59_col1\" class=\"data row59 col1\" >256</td>\n",
       "      <td id=\"T_70445_row59_col2\" class=\"data row59 col2\" >32</td>\n",
       "      <td id=\"T_70445_row59_col3\" class=\"data row59 col3\" >0.965811</td>\n",
       "      <td id=\"T_70445_row59_col4\" class=\"data row59 col4\" >0.745305</td>\n",
       "      <td id=\"T_70445_row59_col5\" class=\"data row59 col5\" >0.932064</td>\n",
       "      <td id=\"T_70445_row59_col6\" class=\"data row59 col6\" >0.981111</td>\n",
       "      <td id=\"T_70445_row59_col7\" class=\"data row59 col7\" >0.980760</td>\n",
       "      <td id=\"T_70445_row59_col8\" class=\"data row59 col8\" >0.995500</td>\n",
       "      <td id=\"T_70445_row59_col9\" class=\"data row59 col9\" >0.763298</td>\n",
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       "      <td id=\"T_70445_row59_col11\" class=\"data row59 col11\" >88.460584</td>\n",
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       "    <tr>\n",
       "      <th id=\"T_70445_level0_row60\" class=\"row_heading level0 row60\" >60</th>\n",
       "      <td id=\"T_70445_row60_col0\" class=\"data row60 col0\" >342840576</td>\n",
       "      <td id=\"T_70445_row60_col1\" class=\"data row60 col1\" >256</td>\n",
       "      <td id=\"T_70445_row60_col2\" class=\"data row60 col2\" >64</td>\n",
       "      <td id=\"T_70445_row60_col3\" class=\"data row60 col3\" >0.967194</td>\n",
       "      <td id=\"T_70445_row60_col4\" class=\"data row60 col4\" >0.763338</td>\n",
       "      <td id=\"T_70445_row60_col5\" class=\"data row60 col5\" >0.939365</td>\n",
       "      <td id=\"T_70445_row60_col6\" class=\"data row60 col6\" >0.981852</td>\n",
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       "      <td id=\"T_70445_row60_col8\" class=\"data row60 col8\" >0.996000</td>\n",
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       "    <tr>\n",
       "      <th id=\"T_70445_level0_row61\" class=\"row_heading level0 row61\" >61</th>\n",
       "      <td id=\"T_70445_row61_col0\" class=\"data row61 col0\" >427775232</td>\n",
       "      <td id=\"T_70445_row61_col1\" class=\"data row61 col1\" >256</td>\n",
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       "      <td id=\"T_70445_row61_col3\" class=\"data row61 col3\" >0.967578</td>\n",
       "      <td id=\"T_70445_row61_col4\" class=\"data row61 col4\" >0.774655</td>\n",
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       "    <tr>\n",
       "      <th id=\"T_70445_level0_row62\" class=\"row_heading level0 row62\" >62</th>\n",
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       "    <tr>\n",
       "      <th id=\"T_70445_level0_row63\" class=\"row_heading level0 row63\" >63</th>\n",
       "      <td id=\"T_70445_row63_col0\" class=\"data row63 col0\" >433083648</td>\n",
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       "      <td id=\"T_70445_row63_col3\" class=\"data row63 col3\" >0.905040</td>\n",
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       "    <tr>\n",
       "      <th id=\"T_70445_level0_row64\" class=\"row_heading level0 row64\" >64</th>\n",
       "      <td id=\"T_70445_row64_col0\" class=\"data row64 col0\" >438392064</td>\n",
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       "      <td id=\"T_70445_row64_col4\" class=\"data row64 col4\" >0.667454</td>\n",
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       "      <td id=\"T_70445_row64_col9\" class=\"data row64 col9\" >0.682447</td>\n",
       "      <td id=\"T_70445_row64_col10\" class=\"data row64 col10\" >0.683275</td>\n",
       "      <td id=\"T_70445_row64_col11\" class=\"data row64 col11\" >84.128167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row65\" class=\"row_heading level0 row65\" >65</th>\n",
       "      <td id=\"T_70445_row65_col0\" class=\"data row65 col0\" >449008896</td>\n",
       "      <td id=\"T_70445_row65_col1\" class=\"data row65 col1\" >512</td>\n",
       "      <td id=\"T_70445_row65_col2\" class=\"data row65 col2\" >16</td>\n",
       "      <td id=\"T_70445_row65_col3\" class=\"data row65 col3\" >0.957437</td>\n",
       "      <td id=\"T_70445_row65_col4\" class=\"data row65 col4\" >0.711106</td>\n",
       "      <td id=\"T_70445_row65_col5\" class=\"data row65 col5\" >0.907937</td>\n",
       "      <td id=\"T_70445_row65_col6\" class=\"data row65 col6\" >0.974444</td>\n",
       "      <td id=\"T_70445_row65_col7\" class=\"data row65 col7\" >0.970784</td>\n",
       "      <td id=\"T_70445_row65_col8\" class=\"data row65 col8\" >0.994900</td>\n",
       "      <td id=\"T_70445_row65_col9\" class=\"data row65 col9\" >0.730851</td>\n",
       "      <td id=\"T_70445_row65_col10\" class=\"data row65 col10\" >0.698136</td>\n",
       "      <td id=\"T_70445_row65_col11\" class=\"data row65 col11\" >86.819930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row66\" class=\"row_heading level0 row66\" >66</th>\n",
       "      <td id=\"T_70445_row66_col0\" class=\"data row66 col0\" >470242560</td>\n",
       "      <td id=\"T_70445_row66_col1\" class=\"data row66 col1\" >512</td>\n",
       "      <td id=\"T_70445_row66_col2\" class=\"data row66 col2\" >32</td>\n",
       "      <td id=\"T_70445_row66_col3\" class=\"data row66 col3\" >0.961624</td>\n",
       "      <td id=\"T_70445_row66_col4\" class=\"data row66 col4\" >0.750031</td>\n",
       "      <td id=\"T_70445_row66_col5\" class=\"data row66 col5\" >0.933016</td>\n",
       "      <td id=\"T_70445_row66_col6\" class=\"data row66 col6\" >0.976296</td>\n",
       "      <td id=\"T_70445_row66_col7\" class=\"data row66 col7\" >0.980681</td>\n",
       "      <td id=\"T_70445_row66_col8\" class=\"data row66 col8\" >0.995400</td>\n",
       "      <td id=\"T_70445_row66_col9\" class=\"data row66 col9\" >0.761170</td>\n",
       "      <td id=\"T_70445_row66_col10\" class=\"data row66 col10\" >0.715214</td>\n",
       "      <td id=\"T_70445_row66_col11\" class=\"data row66 col11\" >88.417909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row67\" class=\"row_heading level0 row67\" >67</th>\n",
       "      <td id=\"T_70445_row67_col0\" class=\"data row67 col0\" >512709888</td>\n",
       "      <td id=\"T_70445_row67_col1\" class=\"data row67 col1\" >512</td>\n",
       "      <td id=\"T_70445_row67_col2\" class=\"data row67 col2\" >64</td>\n",
       "      <td id=\"T_70445_row67_col3\" class=\"data row67 col3\" >0.963506</td>\n",
       "      <td id=\"T_70445_row67_col4\" class=\"data row67 col4\" >0.763462</td>\n",
       "      <td id=\"T_70445_row67_col5\" class=\"data row67 col5\" >0.941111</td>\n",
       "      <td id=\"T_70445_row67_col6\" class=\"data row67 col6\" >0.976667</td>\n",
       "      <td id=\"T_70445_row67_col7\" class=\"data row67 col7\" >0.986857</td>\n",
       "      <td id=\"T_70445_row67_col8\" class=\"data row67 col8\" >0.995900</td>\n",
       "      <td id=\"T_70445_row67_col9\" class=\"data row67 col9\" >0.775532</td>\n",
       "      <td id=\"T_70445_row67_col10\" class=\"data row67 col10\" >0.728312</td>\n",
       "      <td id=\"T_70445_row67_col11\" class=\"data row67 col11\" >89.141842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row68\" class=\"row_heading level0 row68\" >68</th>\n",
       "      <td id=\"T_70445_row68_col0\" class=\"data row68 col0\" >597644544</td>\n",
       "      <td id=\"T_70445_row68_col1\" class=\"data row68 col1\" >512</td>\n",
       "      <td id=\"T_70445_row68_col2\" class=\"data row68 col2\" >128</td>\n",
       "      <td id=\"T_70445_row68_col3\" class=\"data row68 col3\" >0.964659</td>\n",
       "      <td id=\"T_70445_row68_col4\" class=\"data row68 col4\" >0.773287</td>\n",
       "      <td id=\"T_70445_row68_col5\" class=\"data row68 col5\" >0.943968</td>\n",
       "      <td id=\"T_70445_row68_col6\" class=\"data row68 col6\" >0.976667</td>\n",
       "      <td id=\"T_70445_row68_col7\" class=\"data row68 col7\" >0.988599</td>\n",
       "      <td id=\"T_70445_row68_col8\" class=\"data row68 col8\" >0.996000</td>\n",
       "      <td id=\"T_70445_row68_col9\" class=\"data row68 col9\" >0.775000</td>\n",
       "      <td id=\"T_70445_row68_col10\" class=\"data row68 col10\" >0.736927</td>\n",
       "      <td id=\"T_70445_row68_col11\" class=\"data row68 col11\" >89.438827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row69\" class=\"row_heading level0 row69\" >69</th>\n",
       "      <td id=\"T_70445_row69_col0\" class=\"data row69 col0\" >1107252480</td>\n",
       "      <td id=\"T_70445_row69_col1\" class=\"data row69 col1\" >512</td>\n",
       "      <td id=\"T_70445_row69_col2\" class=\"data row69 col2\" >-1</td>\n",
       "      <td id=\"T_70445_row69_col3\" class=\"data row69 col3\" >0.964851</td>\n",
       "      <td id=\"T_70445_row69_col4\" class=\"data row69 col4\" >0.783609</td>\n",
       "      <td id=\"T_70445_row69_col5\" class=\"data row69 col5\" >0.945079</td>\n",
       "      <td id=\"T_70445_row69_col6\" class=\"data row69 col6\" >0.976667</td>\n",
       "      <td id=\"T_70445_row69_col7\" class=\"data row69 col7\" >0.988994</td>\n",
       "      <td id=\"T_70445_row69_col8\" class=\"data row69 col8\" >0.996000</td>\n",
       "      <td id=\"T_70445_row69_col9\" class=\"data row69 col9\" >0.780319</td>\n",
       "      <td id=\"T_70445_row69_col10\" class=\"data row69 col10\" >0.742771</td>\n",
       "      <td id=\"T_70445_row69_col11\" class=\"data row69 col11\" >89.728631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row70\" class=\"row_heading level0 row70\" >70</th>\n",
       "      <td id=\"T_70445_row70_col0\" class=\"data row70 col0\" >602952960</td>\n",
       "      <td id=\"T_70445_row70_col1\" class=\"data row70 col1\" >768</td>\n",
       "      <td id=\"T_70445_row70_col2\" class=\"data row70 col2\" >4</td>\n",
       "      <td id=\"T_70445_row70_col3\" class=\"data row70 col3\" >0.685080</td>\n",
       "      <td id=\"T_70445_row70_col4\" class=\"data row70 col4\" >0.606392</td>\n",
       "      <td id=\"T_70445_row70_col5\" class=\"data row70 col5\" >0.725556</td>\n",
       "      <td id=\"T_70445_row70_col6\" class=\"data row70 col6\" >0.857037</td>\n",
       "      <td id=\"T_70445_row70_col7\" class=\"data row70 col7\" >0.608234</td>\n",
       "      <td id=\"T_70445_row70_col8\" class=\"data row70 col8\" >0.902300</td>\n",
       "      <td id=\"T_70445_row70_col9\" class=\"data row70 col9\" >0.514362</td>\n",
       "      <td id=\"T_70445_row70_col10\" class=\"data row70 col10\" >0.659043</td>\n",
       "      <td id=\"T_70445_row70_col11\" class=\"data row70 col11\" >69.475044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row71\" class=\"row_heading level0 row71\" >71</th>\n",
       "      <td id=\"T_70445_row71_col0\" class=\"data row71 col0\" >608261376</td>\n",
       "      <td id=\"T_70445_row71_col1\" class=\"data row71 col1\" >768</td>\n",
       "      <td id=\"T_70445_row71_col2\" class=\"data row71 col2\" >8</td>\n",
       "      <td id=\"T_70445_row71_col3\" class=\"data row71 col3\" >0.770244</td>\n",
       "      <td id=\"T_70445_row71_col4\" class=\"data row71 col4\" >0.626912</td>\n",
       "      <td id=\"T_70445_row71_col5\" class=\"data row71 col5\" >0.758889</td>\n",
       "      <td id=\"T_70445_row71_col6\" class=\"data row71 col6\" >0.919630</td>\n",
       "      <td id=\"T_70445_row71_col7\" class=\"data row71 col7\" >0.703009</td>\n",
       "      <td id=\"T_70445_row71_col8\" class=\"data row71 col8\" >0.960600</td>\n",
       "      <td id=\"T_70445_row71_col9\" class=\"data row71 col9\" >0.547340</td>\n",
       "      <td id=\"T_70445_row71_col10\" class=\"data row71 col10\" >0.665592</td>\n",
       "      <td id=\"T_70445_row71_col11\" class=\"data row71 col11\" >74.402700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row72\" class=\"row_heading level0 row72\" >72</th>\n",
       "      <td id=\"T_70445_row72_col0\" class=\"data row72 col0\" >618878208</td>\n",
       "      <td id=\"T_70445_row72_col1\" class=\"data row72 col1\" >768</td>\n",
       "      <td id=\"T_70445_row72_col2\" class=\"data row72 col2\" >16</td>\n",
       "      <td id=\"T_70445_row72_col3\" class=\"data row72 col3\" >0.837700</td>\n",
       "      <td id=\"T_70445_row72_col4\" class=\"data row72 col4\" >0.652406</td>\n",
       "      <td id=\"T_70445_row72_col5\" class=\"data row72 col5\" >0.792857</td>\n",
       "      <td id=\"T_70445_row72_col6\" class=\"data row72 col6\" >0.941852</td>\n",
       "      <td id=\"T_70445_row72_col7\" class=\"data row72 col7\" >0.813064</td>\n",
       "      <td id=\"T_70445_row72_col8\" class=\"data row72 col8\" >0.975800</td>\n",
       "      <td id=\"T_70445_row72_col9\" class=\"data row72 col9\" >0.570213</td>\n",
       "      <td id=\"T_70445_row72_col10\" class=\"data row72 col10\" >0.678791</td>\n",
       "      <td id=\"T_70445_row72_col11\" class=\"data row72 col11\" >78.283538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row73\" class=\"row_heading level0 row73\" >73</th>\n",
       "      <td id=\"T_70445_row73_col0\" class=\"data row73 col0\" >640111872</td>\n",
       "      <td id=\"T_70445_row73_col1\" class=\"data row73 col1\" >768</td>\n",
       "      <td id=\"T_70445_row73_col2\" class=\"data row73 col2\" >32</td>\n",
       "      <td id=\"T_70445_row73_col3\" class=\"data row73 col3\" >0.860518</td>\n",
       "      <td id=\"T_70445_row73_col4\" class=\"data row73 col4\" >0.675165</td>\n",
       "      <td id=\"T_70445_row73_col5\" class=\"data row73 col5\" >0.837302</td>\n",
       "      <td id=\"T_70445_row73_col6\" class=\"data row73 col6\" >0.956667</td>\n",
       "      <td id=\"T_70445_row73_col7\" class=\"data row73 col7\" >0.871655</td>\n",
       "      <td id=\"T_70445_row73_col8\" class=\"data row73 col8\" >0.979800</td>\n",
       "      <td id=\"T_70445_row73_col9\" class=\"data row73 col9\" >0.604255</td>\n",
       "      <td id=\"T_70445_row73_col10\" class=\"data row73 col10\" >0.691688</td>\n",
       "      <td id=\"T_70445_row73_col11\" class=\"data row73 col11\" >80.963107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row74\" class=\"row_heading level0 row74\" >74</th>\n",
       "      <td id=\"T_70445_row74_col0\" class=\"data row74 col0\" >682579200</td>\n",
       "      <td id=\"T_70445_row74_col1\" class=\"data row74 col1\" >768</td>\n",
       "      <td id=\"T_70445_row74_col2\" class=\"data row74 col2\" >64</td>\n",
       "      <td id=\"T_70445_row74_col3\" class=\"data row74 col3\" >0.872734</td>\n",
       "      <td id=\"T_70445_row74_col4\" class=\"data row74 col4\" >0.690213</td>\n",
       "      <td id=\"T_70445_row74_col5\" class=\"data row74 col5\" >0.855238</td>\n",
       "      <td id=\"T_70445_row74_col6\" class=\"data row74 col6\" >0.963333</td>\n",
       "      <td id=\"T_70445_row74_col7\" class=\"data row74 col7\" >0.894616</td>\n",
       "      <td id=\"T_70445_row74_col8\" class=\"data row74 col8\" >0.983500</td>\n",
       "      <td id=\"T_70445_row74_col9\" class=\"data row74 col9\" >0.626064</td>\n",
       "      <td id=\"T_70445_row74_col10\" class=\"data row74 col10\" >0.704937</td>\n",
       "      <td id=\"T_70445_row74_col11\" class=\"data row74 col11\" >82.382931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row75\" class=\"row_heading level0 row75\" >75</th>\n",
       "      <td id=\"T_70445_row75_col0\" class=\"data row75 col0\" >767513856</td>\n",
       "      <td id=\"T_70445_row75_col1\" class=\"data row75 col1\" >768</td>\n",
       "      <td id=\"T_70445_row75_col2\" class=\"data row75 col2\" >128</td>\n",
       "      <td id=\"T_70445_row75_col3\" class=\"data row75 col3\" >0.879456</td>\n",
       "      <td id=\"T_70445_row75_col4\" class=\"data row75 col4\" >0.702151</td>\n",
       "      <td id=\"T_70445_row75_col5\" class=\"data row75 col5\" >0.864762</td>\n",
       "      <td id=\"T_70445_row75_col6\" class=\"data row75 col6\" >0.962593</td>\n",
       "      <td id=\"T_70445_row75_col7\" class=\"data row75 col7\" >0.905067</td>\n",
       "      <td id=\"T_70445_row75_col8\" class=\"data row75 col8\" >0.983900</td>\n",
       "      <td id=\"T_70445_row75_col9\" class=\"data row75 col9\" >0.630851</td>\n",
       "      <td id=\"T_70445_row75_col10\" class=\"data row75 col10\" >0.715416</td>\n",
       "      <td id=\"T_70445_row75_col11\" class=\"data row75 col11\" >83.052450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_70445_level0_row76\" class=\"row_heading level0 row76\" >76</th>\n",
       "      <td id=\"T_70445_row76_col0\" class=\"data row76 col0\" >1277121792</td>\n",
       "      <td id=\"T_70445_row76_col1\" class=\"data row76 col1\" >768</td>\n",
       "      <td id=\"T_70445_row76_col2\" class=\"data row76 col2\" >-1</td>\n",
       "      <td id=\"T_70445_row76_col3\" class=\"data row76 col3\" >0.879149</td>\n",
       "      <td id=\"T_70445_row76_col4\" class=\"data row76 col4\" >0.709862</td>\n",
       "      <td id=\"T_70445_row76_col5\" class=\"data row76 col5\" >0.867619</td>\n",
       "      <td id=\"T_70445_row76_col6\" class=\"data row76 col6\" >0.965185</td>\n",
       "      <td id=\"T_70445_row76_col7\" class=\"data row76 col7\" >0.913777</td>\n",
       "      <td id=\"T_70445_row76_col8\" class=\"data row76 col8\" >0.984600</td>\n",
       "      <td id=\"T_70445_row76_col9\" class=\"data row76 col9\" >0.644681</td>\n",
       "      <td id=\"T_70445_row76_col10\" class=\"data row76 col10\" >0.724685</td>\n",
       "      <td id=\"T_70445_row76_col11\" class=\"data row76 col11\" >83.619469</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f76cc110370>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_dir = \"/workspace/svd_subspace/outputs/ViT-B-32/eight_tasks\"\n",
    "moe_data = defaultdict(list)\n",
    "for gate_k in [1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 768, 1024]:\n",
    "    for k in [4, 8, 16, 32, 64, 128, -1]:\n",
    "        file_name = f\"gate_k={gate_k}_k={k}.json\"\n",
    "        file_name = os.path.join(data_dir, file_name)\n",
    "        if not os.path.exists(file_name):\n",
    "            # print(f\"File {file_name} does not exist\")\n",
    "            continue\n",
    "        with open(file_name) as f:\n",
    "            data = json.load(f)\n",
    "        moe_data[\"num_params\"].append(data[\"model_info\"][\"all_params\"])\n",
    "        moe_data[\"gate_k\"].append(gate_k)\n",
    "        moe_data[\"k\"].append(k)\n",
    "        accuracies = {}\n",
    "        for key in data:\n",
    "            if key == \"model_info\":\n",
    "                continue\n",
    "            accuracies[key] = data[key][\"accuracy\"]\n",
    "        average_accuracy = np.mean(list(accuracies.values())) * 100\n",
    "        for key in accuracies:\n",
    "            moe_data[key].append(accuracies[key])\n",
    "        moe_data[\"average\"].append(average_accuracy)\n",
    "moe_data = pd.DataFrame(moe_data)\n",
    "\n",
    "# 使用 Styler 对象并应用背景颜色渐变\n",
    "styled_df = moe_data.style.background_gradient(cmap=\"RdYlGn\")\n",
    "\n",
    "# 显示结果\n",
    "styled_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_1143/3036371907.py:5: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value 'Dense' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.\n",
      "  plot_data.loc[plot_data[\"k\"] == -1, \"k\"] = \"Dense\"\n",
      "'created' timestamp seems very low; regarding as unix timestamp\n",
      "'modified' timestamp seems very low; regarding as unix timestamp\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_1143/3036371907.py:20: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value 'Dense' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.\n",
      "  plot_data.loc[plot_data[\"k\"] == -1, \"k\"] = \"Dense\"\n",
      "'created' timestamp seems very low; regarding as unix timestamp\n",
      "'modified' timestamp seems very low; regarding as unix timestamp\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "matplotlib.rcParams[\"font.size\"] = 14\n",
    "\n",
    "plot_data = moe_data.copy()\n",
    "plot_data[\"method\"] = \"Ours\"\n",
    "plot_data.loc[plot_data[\"k\"] == -1, \"k\"] = \"Dense\"\n",
    "pivot_data = (\n",
    "    plot_data[[\"gate_k\", \"k\", \"average\"]]\n",
    "    .pivot(index=\"gate_k\", columns=\"k\", values=\"average\")\n",
    "    .copy()\n",
    ")\n",
    "\n",
    "sns.heatmap(data=pivot_data, annot=True, fmt=\".1f\", cmap=\"RdYlGn\")\n",
    "plt.xlabel(\"$k$\")\n",
    "plt.ylabel(\"$k_{gate}$\")\n",
    "plt.savefig(\"clip-vit-b-32_hp-acc.pdf\", bbox_inches=\"tight\")\n",
    "plt.show()\n",
    "\n",
    "plot_data = moe_data.copy()\n",
    "plot_data[\"method\"] = \"Ours\"\n",
    "plot_data.loc[plot_data[\"k\"] == -1, \"k\"] = \"Dense\"\n",
    "plot_data[\"num_params\"] = plot_data[\"num_params\"] / 87456000\n",
    "pivot_data = (\n",
    "    plot_data[[\"gate_k\", \"k\", \"num_params\"]]\n",
    "    .pivot(index=\"gate_k\", columns=\"k\", values=\"num_params\")\n",
    "    .copy()\n",
    ")\n",
    "\n",
    "sns.heatmap(data=pivot_data, annot=True, fmt=\".2f\", cmap=\"RdYlGn_r\")\n",
    "plt.xlabel(\"$k$\")\n",
    "plt.ylabel(\"$k_{gate}$\")\n",
    "plt.savefig(\"clip-vit-b-32_hp-params.pdf\", bbox_inches=\"tight\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "'created' timestamp seems very low; regarding as unix timestamp\n",
      "'modified' timestamp seems very low; regarding as unix timestamp\n"
     ]
    },
    {
     "data": {
      "image/png": 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jzxcKMB1tEhHnNg6N93o6htBj92cixWaHLb8QiiJh0s8mYPr8WfC1e2B12hFod0NRpI65thmMgYqIqBdC97hEj+JEBJ+IURzNH4DuDwTv+QlA9fk7go7Xj4DHj4AvgIBfhepXoQY0qKoWPXITJ+jEDz0do0IDSZIQDjodwSb0tRIOPSaTEtyuQDF3PDaZZJgsCsyR280yTCYTzFYZitkEk0mGbCSU8IhD+F1/We4ULgDAnJvf7TQSXdcx6sCRCLRkddqfum9QtxuSOEe8Q/qrsx/niV2eJ7KzjwTvnhvHGZ390HNiO+8dz+1VAIjsyKcyAES2JYUBoNu2xOjUge6ouoB4Hej4gSH2eONxUgEj/Dh031/Hsd0HjMjAEJpK24vAEOf1UB+FR886fmc7//x29zsa+zuR4PcodA5ZgaQoELoGs0WBIkuwOSzGyJ9FASAgyZleNJ2Biogi+N1eKGYzvO0e2Jx2aIEALA5bupvVa7qmxR/F8fmh+QPQfAFoAT90X3DEx2+EHb/Xj4DbF3XPTmhUJxDQoAY0aKoWPXITef9OOOhETF8LBp1Q6BlIkhQ9shMe1TErESFH6dgW90OGOXicYlGMwGQxQo/ZYoKsdIQdSIh63C+jJlL4PxFfRwSK4CehqTApEqadMgMQwPrXI6aRzJ2CaafMMN75hIBkNnUKAFJo+lhXnefg8ZkVAOJ0hFIRAHralj6I6qx39w598LievUMPRAeG2PN1XNOo/NdxvB7Tps7n63ic9JSnuK83NmAEn0d90PG70fn3JPrnOep3Os7ImvFlxHPC+9Fx7shrRuwP/7WSEDP5rvPftc6z8yTj50GSEP55CB0T9eNhTN4LjcyFf5bCxwtASFEBNjS1L/wzHPUzGbkt8uccAIKl8eM+L/L3Jf7Ps6SYYC8th6+pEYrFCsVqC79o3e9DoL0V1oLi6G9DBmKgIiIAgOoPYM0rH3bqeE6fPxMmS2rvBjUqtQWMgOMLQPP5jK/9xte6P2CUvPYHoPtVYyTHG5rC5kfA70fApxmjOn4VqmqM7KgB3ZjGpukJQk/M11rH/Tv6AIcdWZYSjOwYIzVmi9IReIKPzWYFJoupI+xYZJjNJuN5saM8wREi49291HV6eyQ29ER8GRt8wl/IwRELWTbejZRlyIpijEAFt4UfS3L4WMjxH0uSDMgSFFnGxGMPxfT5M+Ft88CWZYff1QbFbHxv8sYd0O/fjpCuA0N379DHmS4U+dzgeaPPp0OPN8IQFTa66gDFCwyx54tsUxcBI+7+zq+X+qBTsI4NwDEd/3ghPvLr8KeOx1K87VEBomO3CAeMDrH5QEQcH7Ut+B8JHdP4Og4Q0Y/DgSHm64ifZyNUJBohQ/TPqK53/JyHfk/Cz4tsNaWCbDZDaDqs+YXw1tfCXb0DkixD6DoseQWwFZcCQgcyfGlfBioigt/txZpXPsSqf70f3maUlza+nnLSVLT9uAO6z6i6pvuMsKMFAlC9xv06Aa8ffp8aMYVNgxpQoap6cGRHN0KP1jFaEzWKE+d+nlAo0ge4syXLUvQ9O51GcUwwW43PJosJZrMCxWyC2WKM2piCwcccOdJjMUVMZ5PDlbCE0NP3zlts8Il6GOwkRYQTSZIhKYoRbpRg8FGUcPAxjosINfECj6R03h75jnAPGaXHteDCoTqEpoUXGxWqCl3XIVusgARYsx2QTQrsThtkkwJrtiMcONqqfojpXHUEhtjOVqf7EboZkYidHkV91MVIXDg4xBxnfIrX8Y9+HP2rEPmLEHrrP/4bBKFdxhv+Use/c6cRg+DBInRwx7ZQHz18SiHCIwhRP0fGzo5jwl/HFggInlfonX+WaeB0MQIdOyWu4xhEjwzHC8bhc8fZFmd0ufPz4vyedBqFi7h2F8fEu15SBThkGa7vN8FeUg57STl0TYWsmBBoc6F163fIGTuuj/8Y/Y+BimiY0gIBuGvq4WlqQeF+e2P962vjHrf+9bWYdupMvLLov2jb3dbpHp6B/v+0okSO7EQGHZMxqmMxwWQxw2I1GaM2FrMRboL7OgJPcMTHbIwQmYOBRzHJkKVghyW4dlDqO8Qd5+tRjIgJPh0VzjqCCSQpPIoTCjuSEvMR2i8rxqhV+OvQOWLDT9+iXvh7qOsQekTgCQQ6HicIRYg8PvgYkY+7+feQFBPy9suHEDqEpgImEyDD6Fxqavh7FHC1GPszQbdBIKLDEnl87OOo50Y+v9MFoz5FTR2K+hy5IY7g/qgpRfEeAx2/TxIiOv7BY2JGrzpdL3IkLn5Lhu3YQeped2RQjRcEIn8W4wSBhJ3ubjr0vQ4CHe1MGAQi2tldhz5eEIgbcLpsX8w26jGhaTBn5aJt2xZIigmy2Qw9EIDQVNhKKgbFG1IMVERDnK6qaK9pQNvOarRV16OpqhGNtS60NHvQ1u6HrbQAJ/ymrOvy0s1t0BQT2tz+Lq8VGtUJVVoLh51QkLGYYLaajQ+bGZbg4+hpbMZnc3AamzEFTobZJAXveUFH0IkMPEAf/+jqxrSCQPAWit6K/B9+xKhLVFBRZEBWIMtyRNAxxXw2RnzijvRIyY3mdKVjQdtggNGMUukiIuTEC0XdBZ7Q1wMi9nsjSZBtNuiaitYfNsNRPsKYlx/88dD9PrRt/wE5Y/eFyZkFzeuJ+IYAImYEoeNT9OOOnBEZBiKO662Yn2OGht5INggk7pjHe16nIBA5WtanIBB5436c63U7TS9BwGEQoEFAUhTYS8sBAL7GWmheDyRFga2kAvbScuP/gRmOgYpoiNBUDe6aOrTuqIF7Vx1aapvQVONCc7MHre1+tLn9aHf7ocZUgXP4BRy5zm7LS08/cQKgBsL365hMMswmGUow6Cihd/9jgk7sfRq9IwCoxqcAoPdluaBQxybyc9T9NjEjOxEjPHIo8JhMkE3GZ0npGO1JdciJxxhpMUKKHhNmehR4tM6BJ/TcAREzdTDy36Kjoxf1gqN+foQIvS4RnE8fQdchgjE49CMmm82QTWYINRD3Xc9QiBWaCt3v6+9X34XIDnaCjnkX77TH65gbX3bdMU/2ep079J2DQGyYCLcn9nlxA07Xz0t8DBENZpIsw15SBntpOYSuGf9vFWJQhCmAgYpo0NFUFe7aRrRtr0JbdQPaG5qxu64FLU0etLUH0OY2wpPPr8V9viRLyM1zoKiiAMV7FKNoRCFUnx8T506JuocqZOLcKdBVFWWFEoQa+sOmBT8AqMZH/Kv1UmTQCX+OGKUJhZiYqWxyaHTHZIJsMgdDj9nYNoCdrY4pbl0EHq3nIzyRzx2QKQ9Sx7TBqAAU8w54uBMdnnoVE350PSoAQugdoUdL8QiLHBmCIx6bTBBCwFpYAm/dLghNhRYxtc9aWBLeby0sCb6sPgSBqFGBmOd1Ci8MAkREsSTFKDwxWEJUJAYqogylqyraaxvR+mMV2nfVw9PYgub6VrQER5za3UZ4cnsCCTuozmwbCsvzUDy6BMUVeSgosiMrywxJdIxMKHYHrHYLps8PrlIep8qfBAHZbIGmqsFOtxzxOTSyE9OxDU9jM0EyBUNPcGTHCEAdxw/ECE+ICBYjMKaz9WKEJzLwJAhFAzPPWwpOHeyofBf+d5Aigk8o9CDilvqIIgqhBSU72h8MPpoOPdD11M4+SRSAQj8zoVG/yHu+Oh0bGfoS/9wITYOtpAwA4Gusg9A0SIoCa2EJbCVlkABY8wv777USEdGwIAmWfgEAuFwu5ObmoqWlBTk5OeluDg0jWkCFu7YBrh+r4N7VAE+TC22729Dc5DFGm4LT9drcgYSlvS1WEwrL81EyuhhFFXnIL3QgL88CkxzqOCcmmUwoPGQC3DVVMOWXwGQ2hwOVGghAbaqDo3yEcewAvWsUNdLRXeDRejbCE3nMgIgJPKFS4HEDENDxOV7Z6lAADIXBcPEGDQiFwv5+HfECUEy1v8QBKOL1D/CojNB1aD4vFKsVuqpCNpmg+XxQrLZB+S4oEdFQZfy/TOqY8of0Lurbm2zAESqiAaL5A1EjTt6mVrhb2uFq9kYFp1a3H4FA/E6/osjIL81F8ahiFFXmIb/Agfx8C6w2GVKnsKV1utVEtligWO0wOZ0wZefA5HBAsdqChQcEXF9+AlNOLiw5uXDtaoHqaoGjYgSErkM2df5z0VXp6p4VLUgcigZEzOgaIsJPRzGIYEU8SY6YthV8/cY3IfTNMMKOQNxpfrqmQgQyLQB1fWw6AlCqSbIMxWIFEBxRhQTFYmWYIiLKIELX4amr6TSbwF7CohREw5Lq9aO9rhFtP1YHg5ML3lYPWl2h4NRxn5PHm7hcc25hFopGFqGosgAFRQ7k5VuRnW2BFJuSAONG/RBJgmw2Q7HZYHJkwZydA5PTCdliTdg5FpIER6UxCuWp3QW3qwWSosBRMQKOyhFQvV60/vBtr0tXp4Qk9SDwhKroKVEV34znI3rNl1BFNqEHS2hrwdDTMeqjBwLB15iuABR6jREBKHL7EA5A/WEwz8snIhpoXS9CDkQt8h15D23Ec6IX/UanRbwjK/SaHE74mhrhrdvV0QZNC39tLylL60hVTzBQESVJ9fjQXtOI1h3VaK+ph3d3K/xtHrhDU/TajWl6RnW9QMLFae1ZNhSPLEJhRR4Kip3Iz7chN88KkxKnYxwZpmKCkyk7B2ZnFmSLJXFwEgJ6wA/N64Hm8UDzuqEH/Mgesw/atm+Fo3wEHJUjg1XQTNADfrRt34qskWOg+/1drtcTN/AoMYEnYSgKBqDI5W5Cf7A7jWbFBKCAL2KEKzMCEGLCEAMQEVF69TwkRKx31mVIiF3YOzok9Oo58YJK5PMjwkh3zw+/cRhxnEBkG2KeE/lGY+TrHyDGmoEHwddYF3e/r7EO9pLyAW1TMhioiLoRcHvRvqsebTtr0F7TAG+TC/42L3xeFe1uf7gkeeg+J1WNP13PZDGhqKIAhZX5KCzOQl6hHfkFNtis3bzrEgpOVhtMTifM2bkwZ2cbVey66IzrqgrN6w4GJyM8qV5Pp3uIFJsduqoi0NKElpYmyBYbFJsNmtcL3W+UUReVo5C1x1ijORFlwkXkH+Pw9DYtYQAKj/xkegBKEIYYgAanTJuXT5QqqQkJMSMNoX0JQkLna8Z0+uM9p6cd/k4hIabTH+85GRgShrx4yy8EK5v2bA22jsey2bi/VWjx+wGhPkSmzzBgoCKC8YfY3+aGu6YBbTtrjeDU3IpAuxeqX0O7JxBTIMIPry9xWfL80jwUVuSjsCQL+YV25Bc4kJXddQCKDU6m7ByYs3KgWCxdt13XoHm9RnjyeqAGA5RQEyzaJElQrDYoNrvx4XBCNhslxoWmQfd3BCkA4Wp9nrpd0L2ejsp4/SVqhCt+0GEAop4a7PPyh6OuQ0LM9KHgcZkfEmJHGjq/hm5DQpxpVpRCnUJC4vXPugsJxnOA8DIJcdaCi7+0QkQbogoWxa4DF3/JhtjnSFLM8+MuAp34NSS8ZooJXQ/3QWKF+gGZjoGKhhUhBPyudrTvqkNbVT3cdY3GiFO7D7qqwetTjWl67UZxiHBZ8gT/38rKdxr3OJVkI7/QgfwCG3LzbTCZuvjljwhOisMJS3YOTDm5UMzmbtuu+7xGaAqOOGkeT5eLksoWa0dwstmh2B2QZAW6L3gOjxuqxw2TzRFeryeWtbDEGE0KBKAH4oS0vgagiOcxAFEqCV2Dp64mI+bld9fh7zYkxOlMd9vhTzok9GBUoLuQ0F2Y6WIEhVIobmcayJSQEN3h70FIiNPObkNGvBGUyNcRbjelj+iyDxL8g5LRGKgo42k+PySTAs0XgGI1Q6gaFGs3ozZCwNfShraqWrRX18Nd3whfUxv87V4IXcAf0Drd59Tm9kPT4v/SWmxmFFUWoLA0B/lFjmB4ssNq7yIESZKxyKzNCpPdCXNODiw5eZB7EpxC9zmFPjweaD5Pws6GZDIFQ5MDpmB4ki1W6GoAmscYufLtboDmdUOo0fdBSYoJkizDVlwKIM56PcWlkGQFjsrRUcUfGIAoXTrK6sdUjNQiKisKAWteQbfz8tt2bO0osMKQMDjE7UwD8TrLsR3+Xk1R6hQSYoJJ6HwMCUR9IslK+D6pwTqbgIGKMpquqnA3tcKenwNvuxd2RYG7yYWsojzIJhOEEPA2udBeVYu26np46puMqXpuH4QuoGl6zHS9AFrb/fAH4k9ZkxUZBWV5KCzLQX6x0yhLXmhHVo4t8f+cJMkINFYbTA4nzNnZMOfmQTF3HfpCr68jOHXc75RwSp0sQ7HZw6FJsTkg22yQAKjB4BRoc8HbUAvN60Wid3VkixWKPRi+7A4IXYeveTdMDifsJQdD11TIigmBNhd8TbthKyiCOSu729dDFClqEeVQ8ImoptjVemHRISlyW8+mnCo2O8xZ2V3Oy498wyHt+hASYkcFug8JsSMNvQ8JUc+P95ykQ0Li193xWoloqJFkGfaSMthLymPud838MAUwUFEG0/zGiNGn73yG9f/5KLzY7MS5kzH1lBnw1TTim6VvQgSntri9avR9Tu0BuL0J7iMCkFOYhcKyXBQUZxkjTkUO5BY4oCgJfnklCbLJBNlqNYJTVjbMOXlQrNZuX4vQ9egRJ68bqqeL+5wgQbHZoqfr2RyQTIox7c/jgep1w9/SbIw6Jeg0SooCxeYIT/cLBbFQGelItsJio2R69Q5Isgyh67DkFcJeOjjeHaLkRQWfqDXBtKgw1BF8IraHi5DED0n9TupYLFmS5fD6WrLJDNlk7nJevmwyw1pYbLzvkFRI6PwchgQiouSEpmAPxj4HAxVlLE0TWPPyB1j1/IrwNm+7F6v+tQIQwP4zD8JX3zeitdWDNncAeqeFbQ02pxWFZXkoKMlCfpEDBYUO5BdnwWJN8OMvAZLJDMVihcnhgCk7G+ZsIzh11/ERQkD3+4x7kyIClO7zJnyObLZAsds7gk9wup7Q1PC75/6mRqjenV2eR7HaoNg7wpNis0M2Jy6h3ullh94dKo14d0gMnneHhoOOaooJFkiO3K5FjvokCkkdYajfhYKPElEwJKZ8fvzS+90c28XPt9C1bufl2wpL+vFFExHRcMBARRlJCAHFpGD96x/F3b/+Px9h6qkz0dQegLvNDwBQzAoKS3ON4FToNMJTSTYcWQlChQRIigmK1QrF7oQ5OwumrFyY7DZIUtchQggBoQaCFfXcUaNPCe9zUoL3OUWEJ5PNDgBQg9P91PZW+Brqupz2JykmY7QpJoSlIvhwAdTUiB98YkZytNhRn+hjO4UhTQfiLeqcat0tnhx83FGOPsH22G1pGIUZCvPyiYgo8zFQUcZpq65DzSdfo3zmBHjb44/IeNu98LZ5MOX4Q6H421BQko2cfAdkOXFwki0WozhEdhZMWTkw2R096lDpmhqxllNHgEo0zQ6yDMVqhBwj9BjBB4oCEfCHR68CrmZj9CpRlT5Jihp1MtkdwWl/Jk4RSpGo9bPijNoILUEY6vLYTAg+EQEowQhPp5CkyMYo0hD72Rrs8/KJiCjzMVBRxvC3ubH1jRVo3lqDdg0YffQ02Jy2uKHK5rTBmevEuPFl0NrbjI2SZNw7YbFAcThhdmbBlJUNk90B2dT9j7rQdWg+b3iaXXi6XsCf8Dmy1RYu7BA9XU8LF5nwN++G6q0yRq8STK2SzGaYbNHT9RRb9yNlqZapC6CKYEW38KiNpkEI436fuNPdEk1t02Lu8RmI6mtxpqqFR22UeNPdupgCFxwNGorBpz8N5nn5RJS5AoEAtERvrlJGURQF5m6qLPcFAxWlna5q2LF8HWo3fAuvN4Dvtu3Grvp2VH72PSacMBkfRNxDFTLxxCnQVA3mnBzYCgqDwckOydTN4rmIuM8puA5TaF2nbu9zCq/lFJxqZ7UBEqD5gvdMudvga6yH5nXHX68JACQ5YuTKET5XTwJff0vFAqhChCq5dTPdLbbIQadKbgMffOLfv9PNdLfY7bEBKbKoARERDQkulwsNDQ3w+RKvA0mZx2q1oqioCDk5OSk/d/p7cTRsCSFQ//m32LH8Y/g9fmyvbsEPO5uNtaAkYNfmKkw/fTYkWcL619Z2VPk7cQqmnzoTikmBZdSYLs8v1EDHQrjh+528CadkRVfF66iwJysm6IFAuDpfoLWm27WhZIul416pUJEIaxfl19OouwVQLTl58DXWJ57uFno80MFH6Wa6W+x2JXYbgw8REfWcy+VCVVUVsrKyUFRUBLO5+zdyqWfCC4kbpVcBpKYKqhACgUAALS0tqKqqAoCUhyoGKkqL1p01+OGNVfA2taGxyY1vt+5Gu8cY1SmpyMX0n+6HvY44FKprNybPnYwZ82fD6/bC5rAh4PUg0LIbckEhJBgjJ0LTglX13FH3OwlNjd8ASYoqRx4aNZJMZkCI8NS/QEsTPDXVcRfEDZNlY7pe1KiTEcIylRACus9rrF3l88JeUt7NAqhl8LuaE38/O5EShpdEIzydp8B1ngbH4ENEROnU0NCArKwsjBgxgv8/SiEhBHQ1YPS1hAhWXDYZy1+k4Ptst9uRnZ2NnTt3oqGhgYGKBjefqx1b31iBlh9r4fEG8O3W3ajf7QYA2J0WTPrJPtj34IpwR9yanwvPriq4m5ugWK1o8flgzcuHvbwS0HW0/ri5R/c5RS2Ga3dAthhrR4lAIFhhzw1/U0NHpb5E5wotiBu+z8kB2dLz0uTpEHlvmOpxQ/O0Q/V4wqN0is0Oa0FRlwugCk2DvawSEHoXISlmZIiIiGgICQQC8Pl8KCoqyuj/76eaSDj7RBiDSYn2df7UeT8ASZKhaypE5O0SQkAEAtCBlIUqSZKQm5uLqqoqBAKBlN5TxUBFA0JXVWx/7yPUffYd1ICGbVUt2FbVAl0XkCQJB04chcNnjYXVboEpOxvZo/eEYrMH15EpgqNiBHQ1ANlkhubzIlQsQXW3h0dNogo7RHxIsmwUifB5jOl6DbXh6X/dLogbHHUy2e1QrPEXxM0kxgLCoeAU/JyolLskG6/Lmd3tAqiSYoKtsHgAXgEREVHqhUOBEAgFARHxGBDRxwgR3CzC/w/1eX0Qug5FUaBrGqJiQtxgIbr4UnR+lGB//HN0tV90dUQ30/O7Ckn9IDhjKNEsIKGqgCl1wScUojRNY6CiwUMIgboN32DH+59A9QVQt9uN77bthsdr/OJUjC7A9J/uh4LiLMg2G7JH7wlzbh4kSYIeCMD1/SY4ykcEC0AYox6634e27T8gZ8994agcFS4YIZtMwYITfmheNwKtLfDU7ep2Yd2oqX92O0w2B6RBMCc6XM49YuRJS/A6JVnpGFkLfo68n6snC6ASDVaZWr2SKBkiooNvdPo7AgGECO6KOSYmTEQdIxA8R4IwkSB8xLtW1DGd2pagvRHXjNe2TtvifA/Cx0S2N/Y1pYBfAAImCL8PemZ3EdJDCv+ni2OkmC/lqNDaSejftLvz9lB/9e0YqKjfuLbvwg9vrISvxY12tx/fbtuNxiZjOp0zx4apR+2LPfcrhWwxw1E5CvbiUmM0Sdfgqa+HrbAYQg2gbdsWYx0psxl6IAChqcaoickE2WI1pus1NxoL43rdiUuTm0wdo002I1goVtugmJ6mq4GI4GR8TrR+lWQyRQQnpzHF0dz1tEQugEpDVSqqV1LqpWK0oCdhImHHu1MHP3H4iOqcx+vgx2tv6Ou4wSHetjiBJM45qD9J4UAgSR2PEXwsQYIsBKACCN4LHOcMwQddddqlmIMTnqWjSfH2xT1H/LU44+3rvLmLNncRlFJVNAKSFP9nXJK6bluGYKCilPO1tOKH/6yAa0c9VFXHDzubsL3aBSEAWZFw8JQxOHT6GFhsFthKy+GoGBEeXfLtroe7pgoiEIBitYZHTYSmQosoiGAtLIEeCKB1yzedGyBJxsK6kdP1bA7I/bj+QKqI4JxhY6pex8hTojLsstnSaeSpJ6Xj4+ECqDTUdFe90l5S1qeRqugONFI/WhCv452y0YLIa8W5Th9GC0TENftztIASCHVAgyEAEeFAigwJwWOliMeQpOChcc4R7xgpshJbdAiJe0zkdWOP765tUe2Pt62b9kc8N7a9Pf1/ptfrRePWrTBZbTDZbD16DvWMZDJF30MVsX0wGBytpEFBC6jY/s5a1H+xBbquY1d9G7Zsb4LPZ9yXM3rvYkw9ehxyi5yw5OUja+QexrxZIeB3tcCza0e4IIRstgACsBWXAug8amIrLoUkyVBsNshma0SFPQcUq3XAF8RNRng9rJiRp0SV9GSLNTjiZO8YeUrxHxougEqDgRCio1x/sGhK6LEeeqwL2ItLu61e6fr+W+N3jqMFGaaj0xzb8e7oJHdsi+28Rz0vXscbXXTwuwgTsR38hJ3zeG1L+JoizxEnoMQNDp2/Bx3PIxpcJEmCbDJDByKq/EkprfLX3xioqM+EEKj95CvsXPkpNL8GV5sPm7ftRlOLcT9PboED044Zh1H7lMDkcCJr5B4w5+QCAFR3O9y7dkJtcwEAJEWBraQC1sIiQNfh2mLcQ2UvORi6pkJWTAi0ueDasgk5e41D7r4Hpe1194YQolOlPc3jCd7b0VmoGmF45MnmyPiCGEQ9IRIEoc7b9Pj7g5+7o9jssOYXdFm9UldVY/S7i8qefdblaEFk57xzBz+lowU9DRNJjRZEvqbIbf07WkBEQ0coVBkFKASCfxAGzd8DBirqk5Zt1dj635XwuTzwBzR8v6MZO3cZ4chkVnDYjD0xfsoYmB02OEeMgrWwGJIkQfP74Kmpgr+p0TiRJMFWVAJbSQVUdztaf9iMnD337foeqgy9qdyotOeJmbbXUaY8SrC6jRGcnOFy7BwhokwjhIgfhLTgYs+aGvwcLxx1PE71yE7ob4FRjTLisdncbfVK2WSGvWIkpPD/uzlaQESULh1/Mwff304GKkqKt7kVP/znfbTubIAQAlW1rfh+ezP8AaPjstcBZZh81L7IznfCUVYJe1kFJEWBrqnw1O6Ct6E23LGy5BXAXjYCgED7jh8QcLUAAALtrV3cQ1WaEVNuhK5BjVdpL17bwgsAd4w8KTbboJieSIOXMU0tGHQ0HUJXg58Thx493ohQgmIvSQsv5NwRhORE4Sj8WIYkm4zPigJIcpehpSfVKy1ZqV3ckYgoE4jg/Zoy36AdEAxU1CuaL4Af31mD+o3fAwJocnmx+cfdcLmMinMFJVmYfux+qNyzCJaCIjgrR0GxWiF0Hd76Gnhqq8PvFpuc2XBUjIRitcFTWx0RsiTYiktgcmbBnJUDQIKvsTbiHqpS2EsHvkKXUaY8ptJeojLlSmSZcmPkSbZY+Y419YoQeuKpb91ti5g6F7zxJzUkqZvQE1zgWTEFPyc4bgB+F1i9koiGk7a2NsyYMQM1NTVoaGjA0qVLcfrpp6e7WcMCAxX1iBACNes2YucHG6AHNPj8KrbsaEZ1TSsAwGIzYeLsvXDApNGw5OTCOXI0zM5so3JfUyM8NVXhMt+K1QZ7xUiYsnIQaGpE69bN4QXdzNm5Rsiy2cPXtpeUwV4aUXlO9H/lOT1epT2/P+6xkskcVWWvJ2XKaWgLF03QNOg9Cj0JglC8aaJ9EDsiFB105AThKGbbIAshrF5JRMNFVlYW1q9fj2uvvRaLFi3C5MmT092kYYOBirrV/P0ObH3zA/jbvNB1gZ21Lny/vRmqanT2xh1SiclH7gtnYQ6claNhyS+AJEkItLXCXb0DmqcdgBE87GWVsBYUQXW3oXXLN9A8bgCAbLXBUTESlpy8TtcPFWPojw6QEAJ6wN+50p6aoEy5xRIsxR4x8jQIyrFTz4TKP/d89CfevURawmIjSZNiR3piRoBips1BUSDHBCHIXU+PG8pYvZKIhguz2YwdO3agsrISe+yxR7qbM2wwUFFCnt0t+OH199G2azcAoLHFg83bmtDWZow0lVTmYsZx+6NkVCGc5ZWwBafQaF4P3Lt2IuBqNk4ky7AXl8FWXAahaWjf/gP8zcY5JVmBrawCtsKSfu/shMqUdwSndmged8IqYLLVFj3yZEt9mXJKHdHrIBQspBB5P1HKiyZInUd/up0uF+e+Id5nR0REPSCEwKpVq3DUUUeluynDCnuH1Inq9ePH/32Ihq+3AgLweAPYsrMZNbVtAAC704LJR+6DfQ8ZCXtJqbEwr9kCPRCAu3o7fI314XNZC4thL62EpCjGPVR1u8I3t1sLimEvq+x2hMd4t1+Kma7TdYU/IQQ0b0SxiODUvfg31ktQbLZgcHIGy5Tbh2WZ8mS+132+ZuyaQvEKJESW0k4wStQfRRPkLoNOd0FIiS41TURE1M82btyIxsZGzJw5M91NGVYYqChM6Dp2ffQlqlZ/Bl3VoWk6dtS14ocfm6BpApIk4cBJozDhJ/sgu6QIjspRMDmcEJoGT00VPPU14U6tOScPjvIRkK02BFqa4K7eAT1g3INkcmbBUWE8tydt8tTVdHlDeVSZ8tDIk9cTf6RBkqJGnFimvENPvtfxnpN49EfrvpR2D9cU6hVJ6j70dFtJbmCKJhAREaXSihUrAAAzZsxIc0uGFwYqAgA0ffcjtr61GoF2H4QQaAhO73O3GyGoYo8CzDhufxSNKkHWiNEw5+YBALyNdfDUVIfvOVIcTjjKR8KclQ3V40br999CbTcKV8hmC+zlI2DJK+hRZ1XoGjx1NVElj4Wmhb825+TCvfPHxItyynLElD1j5Emx2thRjqPb73V2jvHvHBuE+nNNoR5Vkhv8RROIiIhSZeXKlcjNzcVBBx0EAKirq8PChQuhKArq6+vx1FNPwWq1prmVQw8D1TCi+fyQTAo0rx+KzQKhavC7vfh+2Xtor20CALR7A9iyoxl1dcb0vqwcG6YeOw5jDxoBZ+Uo2IpLAEgIuFrg3rUjXDZctliNsJSbD6GpaN+5rWPqnyTBVlIOe0lZL6ePSfA11sXd42usg72kDHrACHKSYoqqsscy5d3TAwGo7naoXjfsxWXdfq81rwciYi2wKHI3FeJC0+e6GDkazkUTiIiIUmHlypWYOnUqZFnGjh078Kc//Qn33HMPrr32Wvz73//GDTfcgMMOOyzdzRxyGKiGCV1VUb1uIxq/+gGy2QQ9oKJw/z1RNmF/aKoOVdWxvb4VP2xrgtAFFEXGwdPG4NCZeyFn5AjjXieTCaq7De7qneFRJ0kxwV5aAWthMSABvoba8EgGEFy0t3wEFEvv3w3pajpYaOpY1qg9IVttkM1mdsa7IHTdmBLpbjNClLs9PAVTsdlhzS/s9nvtHLEHICUYReL3noiIKK02bdqE2tpazJgxA9u3b8f999+Pv/zlL7BYLGhqasLUqVNxwAEHpLuZQxID1TCg+fyo+3IL7MUFOPC8g+BxtcOe40Tz1irUf/U9vHkFWPO/r+D1GKM9o/cpwfSf7o+iPSuNhXltdmg+L9qqfgxX54MkwVZUCltpOWTFBL+rBe7q7eERK8XugKNiFMxZ2Um12d/aArMzC5KixO3oGyMcJpizc5L7pgxh4WqGweCkutsS3lOmWG1QnNmQTeZuv9eW4DRPIiIiyjwrV64EAMiyjL/85S+49957YbFYAAAvv/xySq+1a9cuzJ49G5s3b07peQcrBqphQDIpKBg3BmuXfYj1tz0Lb7sXNqcNE0+YjIknTsGrj78LryeA3AIHph+3P/Y8eAycI0bBnJ0LXVXRXrXdmA4W7JBb8gthL6uEYrFC83nRuv0HBFwtwWuZYC8bAWtBUVKjFprPB3f1dgRaW5A1eiyshSVR9/WEWAtLAKT2/p3BSldVoxBHMDypbnfcqXmSyQST3QmTwwmTIwuKwwFZMf4ECF3j95qIiGgQW7FiBUwmExYtWoR58+bhww8/xBFHHNEv13rnnXcwYsSIfjn3YMRANQwEvAGsXfYhVj2/IrzN2+7FqudXQAA48rxjUPXFtzjwsApkjxptTN8TAp66XfDW7gpP3zNl5cBRMRImuwO6psJdvQPehtpg0JJgKy6BrbQi3EnvDaPC3C5462vC59P8XthLygGgV5XnhjIhdGgejzHy5GmH2t4G3e/rfGCommEwPJkcTshmS8KQK8kKv9dERESD2IoVKzBz5ky8++67ePnll3H88cfj4osvxl/+8pd+udacOXNSft7BioFqGDBZzFj/n4/i7vv4Px/h6qevx4g9C2HPLwBkGf7mRnh2VUXdY+OoGAlzdi6EEPA11sNdsxNCNUZBzNm5cFSMhGKz97ptQohggYvt0P3BsupZ2XBWjAqfz15SBntJeczaSEO/gy+EgB7wB0ee2sMhKt7UPdliDYan4OhTEqXgJVkett9rIiKiwez7779HVVUVLr74YkiShHnz5mHp0qV47LHHwoHq2WefxS9+8QsAgMfjwa233oqioiK43e7wPVZnnnkmVqxYgRdffBH77LMPZFnG0qVL8eGHHwIAXn/9daxYsQJLly7F6aefjt/+9re48847YbPZ8M4772DlypUYMWIEPv/8c1xzzTUYO3Zs2r4nA4mBahjwtnvgbfcm2OeFz+2Ds6gYgVYX3Lt2QPO4AQCy2Qx72QhY8gshSRIC7a1wV23v2G+1wVExEpacvKTapfm8cFfvQKC1JXw9R/lImHPzo0ZSQpUBh3rHXmiaMeoUEaBC5egjSYoCJTx1z/iQTV0vjtxTw+V7TURENJSE7p+KHDXyer0oKSkBAPh8Prz//vvhQDV//nz89Kc/xeWXX47W1laUlZXhhBNOwKpVq3DppZdi7dq1yMnJwc033ww9uMYoAMydOxeHH344Hn74YSxevDhcgv25557Df//7Xzz55JOQJAn33XcfampqGKho6LA5bbA5bXFDlc1pg81hQ/uunfCF7p+RZdhLymErLoMky9D9frTv2hEuSCHJCmxlFbAVliTV8Q6veRSa3hcscGEvKYek9Kas+uAlhIDm80ZV3Uu0npZic8DkdIbvf5K5lhYRERFFWLFiBZxOJyZNmhTeVlRUhPp6Ywmbp59+GgsWLAAALFu2DJ999hleffVVAEAgEICmaZg+fTomTJiAK6+8Ejk5RtGvlpaWTvdhffDBB5g0aVI4TLndblx22WW47rrr8Nhjj6GpqQmzZs3ClClT+vtlZwwGqmHAtaMGE+dOxqp/rei0b+KJU6CpKvyN9QAkWIuKYS+tgGwyG/c11VbDU7cLCL47YS0oNkqom3s/ImJM72uGu3pHeDqhKSsnOL3P1qfXmOnCaz6528KjUIh4xydENlugRIw8meyOXq7dRURERMNNe3s7zj33XJgj+md//OMfceqpp+Lcc8/FwQcfjNmzZwMA/va3v+G4446DEnwTe+XKlZgwYQK++uorbNq0CXPnzg2f4/3338ef//znqGutWrUqfK7Q8xVFwc0339yfLzGjMVANcbu/+R47Pvgck07/KYQw7pkKV/mbOwXTT50JCQKmrGw4ykdAsdoghIC/eXd08HFmwVExCiaHM6l2aD4v2qu2Q21zATCCg6NiJMw5eUNutKWrNZ+iyDJMdke4aESocAQRERFRb7zwwgudtlVUVITvfYq0detWnHLKKeGv33//ffzkJz/B1q1bUVpaGq7e19DQgM2bN2PGjBn48MMPMW3aNADGCFUoZL3zzjtwuVwoKirqdB1VVWEyDY+oMTxe5TClaxq2vr0GzbvbseZ3/8RPfnk0rn76evjcPtgcNqh+P2QZkGQTsvfYCwCgetxwV20PL9wrmy2wl4+AJa8gqeAjdA2e2l0d1QAlCbbiMthLyobEyEuv13yKCE+KzT7kwiQRERFltvHjx4cf19bW4oUXXsDTTz+N4uJiyBG3cvy///f/sP/++8PpdEYFqk2bNmHChAnYuXMntm3bhuOOOw719fXw+XzhaYBvv/022tvbo4LbUMZANYT9+L/VUL0BbPmxCQ273djw37XYZ+I+sDksRpAKeODaUYWcvcYZwaemCr5GY64tJKPimy3J4COEQKClCe5dO6AHjMIK4WqA1sE7vS8Vaz4RERERpcsDDzyA66+/HrIsY/fu3WhsbMS0adNgs9lw8cUX4w9/+ANsNht+9rOf4fPPP8cdd9yBX/7yl+HnX3jhhXj00UdhNptx9dVXQ5ZlLFq0CNdccw3Gjx8Pr9eL8ePH49hjj03jqxxYkhBx3kofhlwuF3Jzc9HS0hK+EW8w8za78MXfX0ZjkxufbKyBJEk4/YrZKCzPh2w2Qw8EIDQVkqIgb/9D0LJpI/SAsZ6RJa8A9vIRUCzWpK6teT1or94Ota1jlMtRMQrmnNxBNSLTX2s+ERER0eDj9XqxdetWjBkzBrYhcu/3iy++iIceegjvv/9+upsyIHrzb9ibbMC3zIeo7195B7qmY8uPTQCA/SeORn5xFoSmQosYUbEWliDQ3go94INidxjBJys7qWsKTYOnrhre+joAkdP7Mn9h2IFe84mIiIhooC1atAjNzc34/e9/D13X8fDDD+OKK65Id7MAALqmAxKg67ox9VAAsjI4+lcMVENQ49db0FbbgtqGdrS0+mC2KDji3J/CatLha6yD0DRIigJrYQlsJWVQPW44RuwBa0FRcvdJhYpY7NoZXjfJmN43Coo1uVGu/pYJaz4RERERDSSXy4UdO3Zg8eLF+Pbbb3HJJZdg3rx56W4WdF1HQ/1u7G5sgqZpUBQFBUX5KCouiLqvK1MxUA0xuqbhx/+tha4LfL+jGQBw+FEHQmpvhKl8BOwlB0PXVMiKCYE2F1p/2IycseMgZSU3zVH1eqKLWFisfVrstz/0as2n0NQ9uzH6JFutnLpHREREQ0ImljbXNSNM1dc1hLdpmob6WuProqKCjB+pYqAaYn78vw8Q8ASws9YFtycAR7YVh8zcG7rPi7ZtWyAppqh7qACjEl9vp6wJTYO7thq+hlpjQ6iIRXAx4FQSugZACrZTASC6LJTBNZ+IiIhoqAqVPxBCBD8ACAGBjq+F8Z/wY4GYr0PPCz8n4jyhD8Q/j7Gth+eJamfM8wAosoyxe++B3Y1NcV/r7oYmFBUX9P83tY8YqIYQb1ML6r/cioCq4YedLQCA6T+fCFnrKKQQew+VpCi9ChFxp/fl5BnV+5IsYtHl9XQdnrqaTlMVQ/dlcc0nIiIiikcIATWgIqCq0FQNqqpCDRifNU1DIKAajyP3aRrU4PbYfZCBsspCNDe1wGz2RISN6OAQGxqiQkpPwka80BJznqHCZLNC1Yx/j3g0Teu4pyqDMVANId8vexdCF/hxlwsBv4aC0hzsfVAZEPBBsTuhedo7PcdaWBq38EI8qscNd/V2qO1tAILT+ypHwZKdm9LXESJ0DZ66GnjrdnVs07Tw12ZnNlq3fcc1n4iIiJIkhICu68EQoUUFDTVgdHRD+9RQuIjaF9qmxQ0hUWEm/Ni4hhY3vHTeF94ep02hx1H7VGObHmd2Sl+UVZbghtsvg8VsgyxlXgdfkiSjryNJkKK+Dj6GFNwG45jQR/BYBPd1e57wuSLPg/D5O58HEdfufH2TyQRFUeKGKkVRMj5MAQxUQ0bjV5vRVtsCjzeAH4OjU7NOmwYEfJBkBc5RY+BvaowZ6SmFvbT7Cny6psJTUw1fY52xQZJhLy2Hrai0n6vbSR3XjOFrrOtYHFiCcc+TMyu89pOkcOoeERGljhCiIzTEdPSjAkVEhz8Q7NgbnfyOfYFQQIkNFREBRYu5Vtx9akTQiR1tiWxbp2AU3d7hRJZlmMxGB95kUmAym2BSgp9NJiim4HaTKWafgoKiPNjsVmRlOWE2GwWqehRaEBNSIsMGor8OPy/iPJ2eh3jnwaB941jXdBQU5YfvmYpUUJQPDIIBOQaqIUDXNPz4zjoAwNZdLui6wMh9ylFRYQc0FZLFgrZtW+CsHAV7aUXHvUhCdBmIhBDwNzXCXbMTQjX+4Jpz8+HowxpVvSF0DSLBELDQjH05++wP2WQetH9EiKj/edxemEwKWlvbkJ2dBVXVYHcMjTVkMlGo4x4aKYg32hCInHqVIBzEjl4k3Bc5StLjfdFTu6JCSECNs09LOCVpqAqFCiUiXIRCiDkqfBhhI/TYHDouGEJCx5kjz2GOeU7UvpjnmEwwmRUoiim8Lxx4IgNQsE0J9wWv25fRjtAaRuWVpUNmHapMICty+D6p3Q2s8kdp8uNbqxDwBNDa7kdVtQsAMGv+VEALQFJM0L0eABIkkxmSLPdoVEn1uOGu+tEo6ABAttrgrBgFc/bALHrsb22B2ZkFSVHihipJUYwCG4Pgl4yI0sfn82PJo89i6ZKX0OpqQ3ZOFhacPw8XXHYWrNb03UcZOdoRNRIRNYUq8b7IENIRWKL3BSLCQGxwiN0XNW1K1aKuGzXaEtOmeKFpKN3f0R1JkmI68p1DiMmkxBkB6QgU5vBxMaMjUedIvC8yhHS9L+KYiH3mBKGJb1TSQJJlGUVFBSgqLoheh2qQ9PMYqAY57+4W1H+1DUIIfF9tTPXbb8reyHVqgN5RCcZWUgaT3dHt+XRVhae2Cr7GemODLMNeUgFbUcmALF6r+X1wV+9AwNWMrNFjYS0sibqHKsRaWIJBMQZMRGnh8/rg9frwzOMvYvEDT4a3t7ra8Oj9T0II4LgTj8Sq99ZGB5bgyEncEZU4+yKnT3WaohUx5Sp63/Ab7YicXqUosaMJsQGgixASCge92hcxQhEnoIRHVOIEje7aO1g6e0SDQag0+mD8vWKgGuS+X/YOhC7Q1OZDfV0bFJOMqccfAuheSIoJQlMhW22wl1Z0eR5jel8D3LuqwuXULbkFcFSMGJBqeELX4W2ohad2FyB0ABI0vw/2knIASFjlj4iGvkBARUtTC5qaWtC8uwXNTS40N7WgaXcLmpta0Ly7Ofw49NlqteCt1c/j2SUvxT3ns0tewvmXnInH/7YUTbtbBvgVJRbquJvNpoQhxBwxVSo2hMQdbQiNQkQGgy72RQaN6BGV0DSseKMtEWEjTgjhaAcRDWUMVINYw8Zv0Vbngi4EtoQW8T3mUNgkLwCEg5FzxB7BEuPx13NS3e1or94OLTi9T7Ha4KgcBXOSi/32VqDNhfaq7dB9RrtNziw4K0dDsdkBAPaSMthLymPazTBFNBhpmgZXSyuad3cEpNgwFLmvuakFra62Xl+nckQ5djc2J3xuq6sNLS2tOOWM49FY39QphJhj7v+IvkFd6RwmutwXf7QlXmgiIqLBh4FqkNI1DdvfXQ8AaGj1oqXJA6vDgkNn7gloXkCSAaHDWlgMc1Z2wvWcbMWlaNux1Qgzsgx7aXB63wCUA9UDAbh37YC/eTcAQDKZ4CgfCUteQdS7maF1shiiiDKLrutoa203gtDu5k4BKSo0BT+7WlqTusdGkiTk5ecgLz/X+CgwPudHfo54nF+QB5vNiuycrLihKjsnC4WF+bjqhotT8a0gIqJhjIFqkPrxrRUIeALQhMDmH4xAMu2kqVA0Y5QHQodkNsNRPrLb9ZwcZZXwtzTBUT5A0/uEgK+xHp6aquCoGWAtLIa9rBKywh9JonQQQqC9zd0xUrS7BU1NzQmm2BkBqaXJlfS9QNk5WeEwlFcQCkZ50QEpYl92TlavR3A8bi8WnD8Pj97/ZKd9C86fB1XVYLaYk2o/ERFRCHuvg5BndxPqv9oOAKhp8cLT7kducQ72O7gYCPjCxzkr9zCq5Ol61+s57XcwLLn5A9J21d2G9qrt0DxuAIBid8BZORomh3NArk80XHg83pjpdM0dYSjBFLtk16NxZjk6h6CYoBTelp+DnLwcmM39/78fu8OGCy47CwCw9PHMqvJHRERDBwPVIPTDsvcgdAENAt99Z1TjmzlvalSYsuQVwJKbB6AH6znpWr9Pp9NVFZ6aKvh2G+2VZAX28kpYC4p5szJRN3xeH5qbXQmm03VMtYucWufz+ZO6ls1uiztKFJpuFzWSVJCLvLwcWDI4mFitFpx38S/wq1+fjdbWdmRnO6GqGsMUERGlDAPVINPwxTdoqzPWmtqx242AX0P52HKM3sMRXnxXUhQ4KkaFnyPJStfrOcn9dyN0eHHgXTs7qgfmF8JRNgKymVNtaPiJrViXqBBD5AiSu92T1LXMFjPyC4zwk5uX08UIknHPUW5+Duz2obdYZWgR34LCPADgND8iIkopBqpBRNc0bF/+CQAgoEjYsik4OnXKxHCYAgBHxaiYsCLSsp6T6vUYiwO3GzeEG9UDR8Ocld0v1yMaaJqmoaW5NTxK1NLk6peKdYCxjk/cQgwJA1Iu7A47R4CJiCht3nvvPfzlL3/BpEmTcOutt6a7Of2GgWoQ2fbf9xHwBCBJEn6oaoEQAnsdvjeK8iVAN0KRKSsHlvzCqOdJsgJbUSmAgVnPSWgaPLXV8DbUhhoAe2k5bMWlA1I9kCgZaatYFzNKFBuQQsdl52QxHBER0aCwbds2PPPMM3j88cexdetWTJgwId1N6lcMVIOEp2E3GjbtAAD4zBK2f98ISZYw7fjxgB68V0KS4By5R6dOV2idJ0dZJez7Hdxv6zkJIRBwNcNdvR16IAAAMOfkwVExEorFmrLrEHWnq4p1sfcbtTS5+lyxLic3O+5okXGPUWoq1hER0fCUaB3RTLbHHnvglltuwbhx4zB//vx0N6ffMVANEj+89h6EJiCbZXz9rTHV7+A5ByPL0nHjuaN8RKfgIoQOd3DR3ECbC5bc/H4pQKH5vHBXb0eg1bi/S7ZY4KgYBUtOXsqvRcOLECJcsS4yIDU390/FuqxsZ3Cto5zuK9YV5CI3LxsmE/+UEhFR6iVaR7Q/Zhj1h4KCgnQ3YUCwFzAI1G/4Cm11rQCAdllGfbULZqsZE47YC4BR2U9xOGENTuuL5Guog+bzQlJMsJdWprxtQtfhra+Bp24XIAQgSbAVlw2aX3SK5nF7YTIpaG1tQ3Z2FlRVC9/QnyqZULEu9n4jY1se8vJzWLCAiIiSIoQAhJ7S83nraxOuI2rcSpGiqeCS3C/TyuVh0hdkoMpwWiCAHSs3AADMWRZ8tM5Yf2rSCRNhQcSaUyM6T/XTA364a6sBwFg0N8XvogdaW9BetR2632iHKSsbzorRUGxDr0rYcODz+bHk0WexdEnP1+vpScW6yIIMTbtb4HH3vWJdtwEpP3fIVqwjIqIMJXQ0bdyQklNJigl5+x3U9TqiJWVo/ubLcBXlvsg/8FBAyuxphJmMgSrD/fjmimAhCqDBp8HV5IEzPwsHHlYGCOM+JVtpBUx2R6fnunftBHQdit0Ba0FRytqkB/xwV++Av6UJACCZzHBUjDSmE/Km+UHJ4/ZiyaPP4tEHngxva3W14dH7n4QQAnOOmYWlS15MWcU6k0mJe79Rfr5RupsV64iIaDiTzWboqtrlOqK6qkI2m6GlIFBR3zBQZTDf7ha07GgAAFiLnPj87W8BANNPmgQlGKYkixX2kvJOzw20t8LfvBsA4KwcnZKOqBACvoZaY9RL14PtKoGjtBISb7AftPw+PxRFxtIlL8Xd/+ySl3H+Jb/AqvfWoGl3S6f9siyHQ1Bufk6XFetC+7KynQxHREQ0tEiyMdKTuhN2uY6obDIjZ69xKbrU8Jia118YqDKQ5vNDMimAyYTxv5qH1p21+PDV1fB5AigcUYSxe2WH5+hmjRrT6V4lIQTcVcbUQGtBEUwOZ5/bFGhvhbtqOzSvMV3L5HDCUTk67sgYZb662gasem8tVi1fg7qaRtz38MKEo02trja4XG24+saLAQHkFeRFBaTsnKxhM0eaiIgoEUmSUjptTuhat+uIZnq1v+GCgSrD6KqK6nUbUfvxN9B8fihWC5x7j8bnqzYBAGaeNBFSMExZCophdnZeJNfXWAfN64GkKLCX9a0Qha4G4N5VBX+TMVImKQoc5SNgyS/iCMMgous6Nn6+CaveW4OV763FNxs3h/flF+SioDAf2TlZcUNVdk4WCgrycPJpxw9kk4mIiIY1SVbCs5AGa5W/4YKBKoNoPj+q121E9erPo7Z9+PKH0AIaRh0wGuVlxj+ZpChwVozsdA49EICnJrIQRXIVy4QQ8O1ugKdmZ3io2ZpfBHt58uekgdXqasOaVeux8r21WLV8LZoam8P7JEnCgYfsh1k/mYKZc6YCEFhw/jw8ev+Tnc6z4Px5UFWN1e+IiIgGmCTLsJcY1ZP7ax1R6ruMDVQtLS34wx/+gOXLl8NutyMQCOCQQw7BrbfeirKysqhj165di1tuuQU+nw9+vx9nnnkmrrrqqkE3giKZFNR+/E3UNlebD7vqjVGDI887BiapFZqnHY6RY+Let+Su2Qmha8FCFMVJtUP1uNFe9SM0dzsAQLHZ4agcDbMzK6nz0cAQQmDb99ux8r21WPneGmxY/wVUtWPedVa2E9NmTcTMOVMx44jJKCzKj3r+BZedBQBY+njPq/wRERFR/wpN6xuMIUoP3nMvhEhzS/pXRgYqt9uNadOmYeTIkfjf//6H3NxcBAIBXHrppZg0aRI+/fRTFBUZVev++9//4tRTT8ULL7yA448/Hk1NTZgyZQo2bdqERx99NM2vpHc0rx9axHo7Qgh8t80oLFFW5ETJiCL4W4xfKGtufqfnB9rb4G9qBAA4Kkb1OlAKTYO7tgq+hmCJTlmGo7QS1qKSQRdOhwu/z4+PP/ocK99bg5XvrsHO7dVR+8eMHYWZc6Zi1pwpOHTieJjNiX/lrVYLzrv4F/jVr89Ga2s7srOdUFWNYYqIiIiSsmPHDgDAzp0709yS/pWRger555/H119/jaeeegq5ubkAALPZjNtvvx2PPfYYnnvuOVxxxRVoamrCueeei2OPPRbHH2/c35Gfn4+FCxdiwYIF+OlPf4qTTjopja+kdxSbBYrVAs3nh8luRbsuwStkSBKwz94lUGwWiPoAsvYY2+m5Qgi4q41CFJb8wl6NJgkh4G9pgrt6B4RqVA+05ObDUTESspmd6UwTWVBizapPotZ1MlvMmDjlEMycMwWz5kzFyNG9u4cutIhvQWFe+HxEREREvVFVVYV58+bh88+N21gef/xxfPrpp7j33ntx9NFHp7l1qZeRgaqx0RhlaWmJLtGcl5cHAOGQ9cgjj6C+vh4nnHBC1HHHHHMMAOAPf/jDoApUQtVQOfNQmLMcyBtTibbmNky51Ild3/wIixaAUDUozqy49zD5dtdD87ghyUbRiLjn1zUAUtQcXF1V0b5zG9S2VgCAbLHCWTkK5uzcfnyl1BuRBSVWvLsGm776Lmp/cUlhOEBNmXE4HE5WXiQiIqL0qaysxNq1a9PdjAGTkYHq2GOPxfXXX49rr70WH374Iex2OwDgrbfewsEHH4wzzjgDALBs2TIAwPjx46OeX1RUhFGjRmH9+vWora1FaWnpgLY/WZIio3j83lj9wiqsv+1ZeNu9sDltmDh3CqbPnwlJAmxFne+L0tUAPDVVAAB7WUXcwCV0HZ66mk5VYmxFJdADAUCSYC8ph624bFDO0R1qQgUlVry7Bh+8/1GXBSX2O3BvTskkIiIiSpOMDFQHHXQQ/vSnP+H666/H0UcfjZdffhkulwvLly/H+++/D4vFAiEEPvvsMwDAqFGjOp2joKAA27dvx+effx4esYrk8/ng8/nCX7tcrn57PT2lqjrWvPQBVv3r/fA2b7vX+FoCpp4yAxZz546zp6YKQtOg2OzBdQmiCV2Dp64mah0DoWnhr50jRkM2maFYbSl/TdQzoYISK95dg1XvrcGGj7/sVUEJIiIiIkqPjAxUAPDb3/4WpaWluOWWWzB58mSMGTMGzz//fHja3+7du6GqKoCOKYCRsrOzw8fFc8899+D222/vn8YnSVEUrH89/vDo+tfWYsb82Z22q+52+HYba0Q5KhMVopDga6yLe15fYx3XMkgTn9eHjz/6PLw2VF8KShARERFRemRsDy1UXnHNmjX44osvcMYZZ+DQQw/Fa6+9hsMOOyxqdMli6Vw4IRS24u0DgBtvvBHXXHNN+GuXy4WRIzuv6zSQvO1eeNu9ife5vXDmOsPbhBBor/oRAGDJK4i7yC9gjFCF1pLqtE/TgvdUMVANhLraBqx8bw1WvbcWaz9IbUEJIiIiIhp4GRuorrjiChx88MGorKxEZWUlVq1ahaOOOgpHHnkkNmzYgLKyMsiyDF3X4Xa7kZUVXdUuNIWvpKTzFDgAsFqtsFqt/f46esPmtMHmtMUNVTanDTZH9JQ83+4GaB63Ud48QSEKwFi/QFKUuKFKUpTw+gaUepqmBQtKGGtDxRaUKCktwoyfTGZBCSIiIqJBKiMD1RtvvIGHH34YtbW14W3jx4/HG2+8galTp+K2227DE088gX322QebNm1CdXU19tlnn6hz1NTUQFEU7L///gPd/KRpqoqJc6dE3UMVMnHuFGiqCsVshB9dVcOFKBylFd2UNxewFpZE3UMVYtxzNbQXWxtora42fLhyHVa+t7bLghKzjpyKcQewoAQRERHRYJaRgertt98GADgc0e/WT5w4EUcddRTWr18PADj55JNxzz33YMOGDVGBqqamBo2NjZg9ezYKCgoGruF9ZLaaMW3edADA+tfXRlX5mzZvOkwRawJ5aqsgNBWK1QZrUfxRuDBJhq3IqHQYW+WP90/1nRACW7f8iJXvrWVBCSIiIqJhJiMD1Z577gkAWLduHebMmRO1T9f18P4rr7wSDz74IJYtW4bTTz89fMwbb7wBALj55psHqMWpITQN7ds2Y+Ix4zH9tJnwtXlhzbLB19yC9m2bkbPXOEiybBSiaKwHECpE0XUgCrQ0wV1bDUfZCNj3OzhqHSqGqeT0tKDE7COn4pAJB7GgBBEREdEQlZG9vIsuugiLFy/GVVddhTfeeCNcFv1f//oXPvroI6xYsQIAUFZWhsWLF+P888/H2rVrMWXKFOzcuRN33nknrr766kG3ErOkKBBqAN7qrfDVmiCbzfBXBSA0NXyvkxAC7urtAABLbgHMWTldnlPoOtw1VdD9Pqiedlhy8xiiklRbU49Vy9di1XtrsWbVx/B6Ou51Y0EJIiIiouEpIwOVw+HAqlWrsHDhQsyZMwdFRUXIyspCZWUlPvvsM4wZMyZ87IIFC5CTk4Orr74aVqsVfr8ft956K84///w0voIkiY57nYSmQtPU8C5rYQkgBPzNu6G6241CFBWJC1GE+Brroft9kExm2IvL+rP1Q05PC0rMPnIaJk8/jAUliIiIiIahjAxUAFBUVISHH364R8fOnTsXc+fO7ecW9T9JUWAvrQAQ516n0goIocO9aycAwF5S3k0himDhijpjKpq9tAKSwmp+3XG1tGLNqvVGQYnla9G0uyW8L1RQYvacqZg5ZwoLShARERFR5gaq4UqSZdhLyo0AFbrXSRj3OrmrdkJoKmSrLVxkoivGSJcGxWaHtaBoAFo/+PS0oMSsI6di+mwWlCAiIiKiaAxUGSg0khR5r5PqccPXWAcAcFaM6vY+KM3ngzd4vL18BEdSIkQWlFjx7hpU7YguJz9m7CjMOnIaZs2ZwoISRERERNQl9hQHASEE3FVGIQpzbj7M2V0XogAAT81OQAiYsnK6LVwxHIQKSqx8dw3WfvBJ3IISs+ZMxawjp2LEqIo0tpSIiIiIBhMGqkHAKETRBkgyHOXdF6IItLfB39IEAHAM09GpqIIS736ITV9vidpfUloUrsjHghJERERElCwGqgwnNK2jEEVpORSLtevjhYBn1w4AgCW/CCb78AkKoYISK95dg9Xvf8SCEkRERETU7xioMpynthpCDUC2WHtUiCLgajbKqksyHGVDY+qax+2FyaSgtbUN2dlZUFUNdoctqqDEyvfWYMP6L6Fp0QUlps+ehJlzprCgBBERERH1CwaqDKb6vPA1NQIAHJXdF6IQekdZdVtxabdl1QcDn8+PJY8+i6VLXkKrqw3ZOVn4xXnz8MsLT8O1l96KtR98EnU8C0oQERERpc+XX36Jm266CStWrICqqjjkkENw3XXX4ZRTTkl30/oNe5sZSOgaAAmSJCFvv4OgetwwO7O7fZ5vd2gRX9OQWMTX4/ZiyaPP4tEHngxva3W1YfEDT0IIgTN+eTI+WfcFJk49FLN+MoUFJYiIiIjSaOvWrZgxYwZ8Ph9KSkpQVVWFNWvWYN68ebjvvvtw3XXXpbuJ/UISQoh0NyITuFwu5ObmoqWlBTk56auKJ3QdnrpdnRf2LSnvcoRKV1W0fPslhKbBUTkatsLiAWx1/wj4Azji8JPQ6mrrtC87JwvvffwKNFVlQQkiIiLqd16vF1u3bsWYMWNgs9kG7LqhN9rD65NCBD9nnpNPPhmHH344rrnmGjgcDtTX1+PCCy/Ea6+9BovFgl27dqGgoCBt7evNv2FvskHXc8hoQAldg6duV3hBXsAoSuGt2wVP3a7gL1R84UV8rbYhs4ivy9UWN0wBxkhVe5ubYYqIiIiGLOON9ho0f/M5mr/+HM3ffA5PXQ2Erqe7aZ14vV7st99+uOWWW+BwGP2z4uJiPPvssygvL4ff78fmzZvT3Mr+wUCVUaTw4r2xjO3xq9JFLeJbMXJIVK/b+v12OBx2ZOdkxd2fnZOF7GznALeKiIiIKD4hBISupexD19Qu32jXNTV110vBhDWr1Yq77rqr03an04kpU6ZAkiSMHj26z9fJRLyHKoMIXQv/wnTap2nBod7OGXioLeK79oOPce2lC3HX/7sRZ557Cv7+4FOdjllw/jyoqgazxZyGFhIRERHFEDqaNm5IyakkxYS8/Q7q8o12e0kZmr/5EkJT+3y9/AMPBaS+TSOUJCnhm/qtra04+uijUV5e3qdrZCoGqgwiyQokRYkbqiRFiTtfVh1ii/i++NzruPvmv0LTNLz9n+W47d7rIcsSlj7eUeVvwfnzcMFlZ8FqHfxVDImIiIhiyWYzdFXt8o12XVUhm83QUhCo+lNDQwPWr1+PdevWpbsp/YaBKqMIWAtL4K3b1WmPtbAEQPRwrBAiXCbdkl84qBfx1XUdf71nMZ78+78AAMefdDRuv/d6WKwWnHfxL/CrX5+N1tZ2ZGc7oaoawxQRERFlFkk2RnpSd8Iu32iXTWbk7DUuRZfqv7uAbrvtNtx3333YZ599+u0a6cZAlUEkWYG9xBgK7UmVP2MR37bgIr6V6WhySrjdHtx09V147+0PAACXXXMeLr7ynPBom91hVGEpKMwDAE7zIyIioowjSVKfp81FErrW7RvtmVrtL+Q///kPCgsL8atf/SrdTelXDFQZRpJl2EvKYC8pjymPGR2mhsoivnW1Dbjygpvw9Zffwmwx4477bsDxJx2d7mYRERERpVVv32jPNB9//DE++eQT3H777eluSr9joMpAoXcbuvpFGQqL+H779RZcfv7vULurHvkFubj/73fj0IkHpbtZRERERBmhp2+0Z5pPPvkEy5cvx8KFC9PdlAGR2f8aFJeuqvDUVgMA7KWVkJTMHu6NZ8W7H+KX8y5H7a56jBk7CktffZRhioiIiCiGJCuQZBmyyQxJljN+mt/777+PNWvW4Le//W3U9ra2Nlx55ZXwer1paln/STpQ/f73v09lO6gXBvMivkIIPPP4i7jqwpvhcXswefrhePqVRzBiVEW6m0ZEREREffDMM8/gxBNPxEMPPYRx48aFP/baay+UlJSgrq4ONpst3c1MuaSn/N19990wmUy44oorUFBQkMo2URc0f8QivuWDaxFfVVXxp9sW4fmnlwEATjnjeNx81zUwmznzlIiIiGgwe+yxx3DhhRcCAL799tu4xyxYsGAgmzRgkh6hslqt+Pzzz3HYYYfhnHPOwdq1a1PZLkrAs6squIhvNszZg2cR37bWdlxx/o14/ullkCQJv7nxEiz8428ZpoiIiIiGgAsuuABCiC4/5s6dm+5m9os+Tfl7+eWXsWXLFhx//PG46aabcPjhh+Of//wnPB5PKttIQaq7Df6W3QAAxyAanareWYNfzvs1Vq9YB5vNir88egfOu+TMQdN+IiIiIqJEkg5UN910EwDAZDLhtNNOw3vvvYelS5fiq6++woEHHoirr7464XAf9Z4QAu7qwbeI75effYMFJ12KLd9uRXFJIZa88CCO/OmsdDeLiIiIiCglUlrlb+zYsRg3bhx0XceDDz6I8ePH48gjj8SLL74IXddTealhZzAu4vt/b7yP80+7Eo31u7HPfmOx9NVHccD4FK3oTURERESUAZIOVG+++Wb4sdfrxYMPPoixY8fisssuQ11dHa644gp8//33ePjhh7Fq1SpMmDABy5cvT0mjh5vBtoivEAKPPbIU1122ED6fH7PmTMWTLz6EsoqSdDeNiIiIiCilkq4IcMEFF+DZZ5/Fhx9+iEWLFqGurg7Z2dm44YYb8Jvf/AbFxcXhYx944AF8//33mD59Op577jn85Cc/SUnjh4vBtIhvwB/AnTf9Pyx7wQjcvzhvHn77+19DGYRrZRERERERdSfpQFVTU4MjjzwSQggUFxfjzjvvxOWXX46cnPiV58aOHQubzYbrrrsOn3zySdINHm50bfAs4tvS7MI1F/8e69d+BlmWccPCK3Dmuaeku1lERERERP2mTzWrc3JysHDhQlx88cWw2+1dHrtz505s374dzc3NfbnksDNYFvHdvm0nfn3e7/DjDzvgzHLg3ocWYuZPpqS7WURERERE/SrpQOV0OvHpp59izJgxPTq+oqIC5557LqZOnZrsJYcdLeCHr8kok24vH5GxZcY/Wfc5rv7VLWhpdqG8shSLHr8H+4wbm+5mERERERH1u6QD1fLly3scpgBAlmU8/vjjyV5uWBG6BkACBJA37kCobjdMzqx0Nyuu119+GwuvvxdqQMWBB4/Dg//8A4pKCtPdLCIiIiKiAZF0oJowYQJeeeUVbNy4Eb///e8BAD6fD/fccw/23ntvLFiwIGWNHE6ErsNTVwNfYx2EpkFSFFgLS2ByOIEMGqESQuCRvzyOxQ8+BQA46rjZuPuvN8Fut6W5ZUREREREAyfpsukvvfQS5s2bh9tuuw3t7e0AAKvVittuuw3vvPMO5s2bh0AgkLKGDgdC1+Cp2xW+bwoAhKbBW7cLnrpdwZGr9PN5fbjhyjvCYeqCyxbgz4/cxjBFRERERMNO0oHqj3/8I6ZOnYpFixbB6XRG7fvLX/6C119/HXfccUefGzi8SPA11sXdY2xP/whVY0MTLjzzN3jrtfdgMim4/d7rcdUNF0GWU7pGNBERERHRoJD0lD+v14v169fH3Zefn4/KykosWbIEd955Z9KNG26EroVHpjrt0zQIXYOUxuDy/eZtuPz836Fqxy5k52Thr4vvxKRph6WtPURERERE6ZZ0oCopKUm4r6WlBTU1NRlblS5TSbICSVHihipJUSDJ6VuDau0HH+PaSxei1dWGkaMr8dCSP2LM2FFpaw8RERERUSZIerhjxIgR+OCDDzptDwQCuOiii+Dz+XDooYf2qXHDj4C1MH5QNbaLgW1O0IvPvoZLf3k9Wl1tOHTiQXhm2SMMU0RERERE6MMI1S233IJp06bh7LPPxvTp02E2m7Fx40YsXrwYO3fuhKIovIeqlyRZgb2kHAA6Vfmzl5QP+HQ/TdPw13sW46l/PA8AOOHko3Hbn66HxWoZ0HYQEREREWWqpAPV3nvvjddeew2/+MUvcP/990OSJAhhjKDk5+fjb3/7G4488siUNXS4kGQZ9pIy2EvKg/dMKQDEgIcpt9uDG6+6C8v/zxiF/PU15+OiK3/JaZxERERERBGSDlQAMHXqVGzevBnvvPMONm7cCCEE9t57bxxzzDGdKv9Rz4XulUpXAYq62gZccf6N+GbjZlisFtxx3w342c+PSktbiIiIiGjwWr16NebMmYPFixfj3HPPTXdz+kWfAhUAmM1mHHfccTjuuOOitj/22GM488wz4XA4+noJGkCbvvoOl59/I+pq6pFfmIcH/n43DplwYLqbRURERESDzI4dOzBv3jz4/f50N6Vf9dsQSGlpKX7961/31+mpH6x490Occ+oVqKupx557jcbSZX9jmCIiIiJKI2PpHB26GoDQ9YRL7GQat9uNM888E6eeemq6m9Lvkh6h2rZtG8455xx88skn8Hg8cY9xOBxYsmRJ0o2jgSGEwNIlL+HPdz4MXdcxZcbh+PMjtyMnNzvdTSMiIiIatoSuw1O3K6ZYWSnspQNfrKy3LrjgAlx11VVob29Pd1P6XdKB6rrrrsOHH36I/fbbD7quQ5IkFBUVATA66N9++y2uuuqqlDWU+oeqqvjTbYvw/NPLAADzzjwBN935G5jNfZ4NSkRERDRsCCEAXU/d+SDgrauBt25XxzZNg7euGoCAraQMElJULEyWU1p47O6778Z+++2H+fPn44knnkjZeTNV0r3mdevWYcOGDTjwwAOxY8cOPPTQQ/jTn/4U3n/BBRdgwYIFKWkkpYbH7YXJpKC1tQ3Z2Vnw+fz4892P4OXn/gNJknDNTZfil786jZX8iIiIiHpL19G08dOUnEpSTMjbbzx8jXVx9/sa62AvKUfzN19AaGqfr5d/4GGAovT5PADw2muv4euvv8bSpUtTcr7BIOlANWbMGBx4oHF/zciRI7F161Z4vV7YbDYAwIIFC3DTTTfh6aefTk1LqU98Pj+WPPosli55Ca2uNmTnZOHMc0/Blb/9Fb7+4ltcctU5mHPszHQ3k4iIiGjYk81m6Kqa8H4poWnQNRWy2QwtBYEqVb766issWrQIr7/+erqbMqCSDlQ+nw/19fUoLi4GAJxyyilYuHBheJSqpaUF//vf/1LTSuoTj9uLJY8+i0cfeDK8rdXVhr8/+BQA4JEn/oSiksJ0NY+IiIho8JNlY6QnVSQJkqLEDVWSokA2mZGz136puVYK7sfavXs3fv3rX+Nf//pXeIBluEg6UP3sZz/DnnvuicrKStx///2YP38+7rjjDmzbtg3l5eV48sknYbfbU9lWSpLJpGDpkpfi7nvuiZdx8RW/HOAWEREREQ0tkiSlbNocYIxCWQtLg/dMRbMWlgJCQErh9fpq4cKF2LhxI4444oio7S0tLQCAG2+8EX/84x9xzz334OSTT05DC/tP0oHqhhtuwPfff49ly5ahpaUFiqLg6aefxlFHHRX+xt1xxx0payglr7W1Da2utvj7XG1obW1HQWHewDaKiIiIiBKSFAX20nIAgK+xNuOr/LW2tqKxsRGNjY1x99fU1KCmpiacE4YSSQghUnnCXbt24YMPPsC4ceNw0EEHpfLU/crlciE3NxctLS3IyclJd3NSKuAP4IjDT4obqrJzsvD+J8tgtpjT0DIiIiKiwcHr9WLr1q0YM2bMgE5pE5oGSBKErkGSlYwbmerOE088gfPOOw9LlizBueeem9a29ObfsDfZIOloe9ppp+GUU07ptL28vBzz588fVGFqqFNVDQvOnxd334Lz50FVB8cCcURERETDjaQokGQZsskMSZYHVZgaLpIOVG+++SZUNXOqilBidocN5158Ji668pfIzskCYIxMXXL1ObjgsrNgdwyvGweJiIiIiFIl6Xuo5s+f3+06U5deein+9re/JXsJSqE/LnwARxw1He+ufxnudg+ys51QVQ1WqyXdTSMiIiIiGrSSHqF65JFH8O677+KLL77otE8IgQ8++ABPPfVUnxpHqfH1l5ux7N9v4tpLF6KpsRkFhXkwW8wcmSIiIiKifnXuuedCCJH2+6f6U9IjVCUlJWhvbw+vO0WZ64m/PwcAOPaEn6C8sjTNrSEiIiIiGjqSDlTHHXcc3nnnHey3334wmztXiNuxYwe2bt3ap8ZR3+3cXo3/+8/7AIBzLz4jvY0hIiIiIhpikg5U8+bNw9VXX42pU6fG3R8IBLD33nsn3TBKjaf+8W/ouo5psydh3AH89yAiIiIiSqWkA9Xxxx+P1tbWhPvb29t5D1Wa7W5sxrJ//xcAcN7FZ6a5NUREREREQ0/SgcrpdMLpdCbcv3nzZvj9/mRPTynw3JMvw+v1Yf+D9sWkaYemuzlERERERENO0oHq/PPPT7jP7/dj/fr1mD17No466qhkL0F94HZ78K8nXwEAnH/pmZAkKc0tIiIiIiIaepIOVE888US3xzQ2NuLvf/97spegPlj2/H/R0uzCiFEVOPKns9LdHCIiIiKiIalPU/5ef/11jBkzptO+HTt24KWXXsLVV1/dl7ZRkgIBFU/9898AgHMuOh2KoqS5RUREREREQ1PSgWrBggU44ogj4u4bPXo0Vq9eja+++gqjR49O9hKUpP97Yzmqd9YgvzAPP59/XLqbQ0REREQ0ZMnJPvHRRx/tcv+xxx6LW265JdnTU5KEEHhi8b8AAAvOnQebzZrmFhERERERDV1JB6rufPLJJ9i0aVN/nZ4S+HDlenz79RbYHXac/suT0t0cIiIiIqIhLeVV/oQQqKqqwvLlyzFx4sSkG0bJWfLocwCAeWeegNy8nDS3hoiIiIhoaOu3Kn+HHnoolixZkuzpKQlffbEJ6z78FCaTgrMvmJ/u5hARERERDXl9qvL36quvYuzYsVHbFUVBXl4esrKy+tw46p3Q6NRPTzwS5ZWlaW4NEREREdHQl3SgmjdvHubMmZPKtlAfbN+2E++8uRIAcO7FZ6S5NUREREREw0PSRSlCU/7a2trC23w+H9auXdvnRlHvPfmP56HrOmYcMRn7jBvb/ROIiIiIiKjPkg5U9fX1OPTQQzFq1CgEAgEAgNVqRUtLC6ZPn46PP/44ZY2krjXW78arL7wFADj/0l+kuTVERERENFy1tLTghhtuwKRJkzB79mxMmzYNl112GWpqatLdtH6T9JS/m2++GZ9//jkqKyshSVJ4+7HHHgtZljFz5ky8//77mDx5ckoaSok99+Qr8Pv8OPCQ/XD45IPT3RwiIiIiGobcbjemTZuGkSNH4n//+x9yc3MRCARw6aWXYtKkSfj0009RVFSU7mamXNIjVO+++y7efPNN/PDDDzCZonPZ0UcfjaysLNx00019biB1zd3uxr+eegUAcN7FZ0aFWyIiIiIa3ISmQeg6dDUAoesQmpbuJiX0/PPP4+uvv8bdd9+N3NxcAIDZbMbtt9+OHTt24LnnnktzC/tH0iNUI0eOxLHHHptwv9lsxpo1a5I9PfXQS/96A66WVoweMwJzjp2R7uYQERERUYoIXYenbhd8jXUQmgZJUWAtLIW9tBySnPS4SL9pbGwEYEz7i5SXlwcA4ZA11CT9L2E2m+Hz+eLu+7//+z/U1NSEv3nUPwIBFU//898AgHMuOh2KoqS5RURERETDkxDCGE1K0YeuqfDUVsNbtys8KiU0Dd66anhqq6FrauquJ0RKvgfHHnssJEnCtddeC4/HE97+1ltv4eCDD8YZZwzNStR9Kpt+5plnYvHixSguLgYABAIB/POf/8SNN94ISZJw+umnp6yh1Nlbr7+Lmuo6FBYXYO4piUcLiYiIiKif6TqaNn6aklNJigl5+42Hr7Eu7n5fYx3sJeVo/uYLCE3t8/XyDzwMSMEb8wcddBD+9Kc/4frrr8fRRx+Nl19+GS6XC8uXL8f7778Pi8XS52tkoqQD1SWXXILly5dj1KhR2GuvvWA2m7Flyxa0t7dDCIGJEyfirrvuSmVbKYIQIryQ74Lz5sFqs6a5RURERESUCrLZDF1VE94vFRrBks1maCkIVKn029/+FqWlpbjlllswefJkjBkzBs8///yQnrmWdKACjBvP/v73v+Oxxx7Dxo0bIYTAgQceiNNPPx3XXHMNbDZbqtpJMT54/yNs+XYrHE47Tjvr5+luDhEREdHwJsvGSE+qSBIkRYkbqiRFgWwyI2ev/VJzrRTejxWaPrhmzRp88cUXOOOMM3DooYfitddew2GHpfD7k0H6FKgA4KKLLsJFF12UirZQL4RGp079xYnIyc1Oc2uIiIiIhjdJklIybS5EaBqshaXw1lV32mctLAWEgJSB989fccUVOPjgg1FZWYnKykqsWrUKRx11FI488khs2LABe+yxR7qbmHJ9iqNutxtbtmwJf+3z+fDCCy9E3YRGqffFhq/x8drPYDIpOOuCU9PdHCIiIiJKMUlRYC8th62kIhycJEWBraTCqPKXgWHqjTfewMMPP4yf/7xj9tT48ePxxhtvoLW1Fbfddlv6GtePkg5UW7duxb777ovx48fD6/UCAKxWK/bff3/MmjULr776asoaSdGeWPwvAMDPTjoaZeUlaW4NEREREfUHSZZhLylD3v6HIO+AQ5C3/yGwl5RlZMl0AHj77bcBAA6HI2r7xIkTcdRRR2H9+vXpaFa/S/pf43e/+x2qqqpw4IEHwmrtKIhwwAEH4G9/+xvmzZuHN998MyWNpA7bftiBd99aCQA49+KhWXqSiIiIiAySokCSZcgmMyRZzsiRqZA999wTALBu3bpO+3RdD+8fapIOVJ988gm++eYbrFu3zpgzGmHChAkoKSkZssN66fTUP56HEAKzjpyKvfYZk+7mEBEREREBMGorjBs3DldddRW2b98e3v6vf/0LH330Ee688840tq7/JF2UYuTIkdh3330T7g8EAvjiiy+SPT3F0VDXiNdeMoZSz7vkzDS3hoiIiIiog8PhwKpVq7Bw4ULMmTMHRUVFyMrKQmVlJT777DOMGTM0BwOSDlRWqxUulws5OTmd9j3zzDNobGzE6NGj+9Q4irb0iZfg9/lx8GEH4LCJ49PdHCIiIiKiKEVFRXj44YfT3YwBlfSUv/PPPx/HHXdc1ChUdXU1brjhBlxwwQWQJAnnnXdeShpJQHubG/9+2ij0cd4lZ3aaZklERERERAMv6RGq0047DevXr8chhxyCrKwsmEwmtLS0ADAW9Jo7dy5uvvnmpM7tdrtRWVmJ5ubmuPtlWUZdXR0KCwsBAGvXrsUtt9wCn88Hv9+PM888E1ddddWQCh0vPfc6Wl1t2GPsKBxx9PR0N4eIiIiIiNDHhX3vu+8+HH300fjnP/+Jr776CmVlZdh7771x+umn4xe/+EXS53322WfR3NyM0tJS5ObmRgWjXbt2YcKECeEw9d///hennnoqXnjhBRx//PFoamrClClTsGnTJjz66KN9eXkZI+AP4Kl/vgAAOPeiMyBnaKlMIiIiIqLhpk+BCgCOOeYYHHPMMXH3ud3uTnXoe+KNN97ARx99hEmTJnXaN27cOJx99tkAgKamJpx77rk49thjcfzxxwMA8vPzsXDhQixYsAA//elPcdJJJ/X6+pnmv6+9i7qaehSXFOKEk49Od3OIiIiIiCioX4c6pkyZ0uvntLW14fbbb48bptavX4/t27dj3rx5AIBHHnkE9fX1OOGEE6KOCwW8P/zhD0m0OrPouo4nHn0OALDgglNhsVrS3CIiIiIiIgrpt0D15JNP4quvvur187KysjB+fPwKdk8//TR+/vOfIzs7GwCwbNkyAOh0fFFREUaNGoX169ejtra2123IJKuWr8X3322DM8uB+b84Md3NISIiIiKiCCkPVKtWrcLRRx+N888/P6XnVVUVzz//fHi6nxACn332GQBg1KhRnY4vKCgAAHz++edxz+fz+eByuaI+MtGS4OjU/AUnIjsnK82tISIiIiKiSCkLVK+88gqmTZuGI444Au+++y6EEKk6NQDg7beNBW1D0/l2794NVVUBALm5uZ2OD41i7d69O+757rnnHuTm5oY/Ro4cmdL2psK3X32HrVt+hMlswlkXzE93c4iIiIiIKEafApXf78c//vEPjBs3DqeeeirWrl2LPfbYA3fddRdeeOEFOJ3OVLUTzzzzDM444wyYTEYdDZ/PF95nsXS+rygUtuLtA4Abb7wRLS0t4Y8dO3akrK195XF7EfAHkJOfg7dWP4+nXnwIJaVF6W4WERERERHFSKrKX0tLCx555BEsWrQofI9Sfn4+Hn/8ccydOzdc5nz58uUpaWRrayteffVVrFixIrytoKAAsixD13W43W5kZUVPhwtN4SspKYl7TqvVCqvVmpL2pZLP58eSR5/F0iUvodXVhuycLCw4bx723m8srCxIQURERESUUXo1QlVVVYVrr70Wo0aNwi233IK6ujqcfvrp+Oyzz3DQQQfhxBNPjFoz6qGHHkpJI1966SWMGjUKEydODG+z2WzYZ599AADV1dWdnlNTUwNFUbD//vunpA0DweP24rGHn8GjDzyJVlcbAKDV1YZHH3gSjz3yDDxub5pbSEREREREkXocqM455xzsueeeuP/+++H1enHeeedh06ZNePbZZ3HQQQdFBalUe/rpp8PFKCKdfPLJAIANGzZEba+pqUFjYyNmzJgRLk4xGJhMCpYueSnuvqWPvwSTSRngFhERERERUVd6HKiuvPJKnHDCCZAkCXfccQf+8Y9/YK+99urPtgEwRsVWrFiBBQsWxG2T0+kMl08PeeONNwAAN998c7+3L5VaW9vCI1Od9rna0NraPsAtIiIiIiKirvQ4UB1++OF46aWX8NVXX2Hz5s04+OCD8fTTT0PX9f5sH5YuXYpp06Zhjz326LSvrKwMixcvxssvv4y1a9cCAHbu3Ik777wTV199NY4++uh+bVuqZWdnJSyNnp2Thezs1BX5ICIiIiKivut1lb99990Xjz32GN58801s2LABhx9+OJ544glomtbp2La2+KMtvfHMM8/grLPOSrh/wYIFePHFF3H11Vdj9uzZmD9/Pm699Vb89a9/7fO1B5qqalhw/ry4+xacPw+q2vl7TERERERE6SOJPi4YtXv3bixatAiPPfYYrrzySvzqV78Krws1ceJErF+/PiUN7W8ulwu5ubloaWlBTk5O2trh8/nx2CPPYOnjEVX+zp+HCy47i1X+iIiIiNLE6/Vi69atGDNmDGw2W7qbQ0nozb9hb7JBnwNViNvtxt///ncsXrwYs2bNwtixY3HzzTcjEAik4vT9LlMCFWBU+zOZFLS2tiM72wlV1WB38BeXiIiIKF0YqAa//gpUfVrYN5LD4cDVV1+NL7/8EgcffDDuu+++fr+/aqiyO2wwW8woKMyD2WJmmCIiIiKiQee9997DCSecgDvuuKPbYzVNw/PPP4+zzz4b1157bbiy+GCQ1MK+XZ7QZMJll12G4447DgcddFCqT09ERERERBls27ZteOaZZ/D4449j69atmDBhQpfHb9q0CWeccQYOO+wwPPjgg8jPzx+glqZGykaoYo0ZMwZ33313f52eiIiIiGjIE5oGoevQAwEIXYeIUwgu0+yxxx645ZZbcO+993Z77OrVqzFx4kSccsopePzxxwddmAL6YYQq0lVXXdWfpyciIiIiGrKErsNTWw1vfS2EpkFSFNiKy2Avq4Ak99u4SMoUFBR0uX/Tpk342c9+hqOOOgq33nrrALUq9fo1UBERERERDQdCCCCF9QOEEPDW7YKnprpjm6bBU1MFALCVlEGSpNRcTJZTd66o0yYOfUIIXHTRRXC73fh//+//pfzaA4mBioiIiIior3Qduz//OCWnkkwm5B9wCLz1tXH3e+trYC8tR9NXn0Goap+vV3DwBEBR+nye3li+fDlWrVqFWbNm4X//+x9Wr16Nzz//HAUFBbj88ssxb178tVkzUeaPFRIRERERDSOyyQxdDSS8X0poGnRVhWwyD3DLUuf5558HAGRnZ2PWrFl46qmn8O6770KSJJx66qm4//7709vAXujzCFV7ezt++OGHcEW/nTt3YsSIEX1uGBERERHRoCHLxkhPqkgSJEWJG6okRYFsNiN33wNSc6003I+1ceNGAMBvf/tb7LfffgCAoqIiPPnkkxgzZgxuvPFGnHXWWSgqKhrwtvVWn757t912G4qLi3HSSSeFt61evRo//elP8eWXX/a1bUREREREg4IUDECp+oAQsBWXxb2WrbgMECJ11+uH+6e609DQAAAoKSmJ2j5y5EgcddRR8Hq9WL169YC3KxlJB6pFixbhjjvugNfrNW7CCzr99NNxww03YPLkyVi3bl1KGklERERENJxIigJ7WQXsZZVGwApvqzSq/A3wPU+pFqoA6PF4Ou3bZ599Eu7LRH0KVDfddBNcLhdGjx4dte8nP/kJcnNzccMNN/S5gUREREREw5Eky7CXliP/oMPCH/bS8kFRMr07M2fOBAB88sknnfYpwbAYuqUo0yX9ryFJEu666y5kZWXFHSaUJAkfffRRnxpHRERERDScSYoCSZYhm82QZHlQjUzpwTLykbPZQi655BJYrVY88cQTnfZ9/PHHmDlzJg44IEX3iPWzpANVaCgunrVr16KmpgbZ2dnJnp6IiIiIiAaxHTt2ADCK1sXac8898fDDD+PDDz/EvffeG96+ePFifPfdd3j88ccHrJ191adA9cEHH3Tavn37dpx99tmQJAlz587tU+OIiIiIiGhwqaqqwpQpU3DJJZcAAB5//HEceuih+N///hd13AUXXIA333wTr7zyCg477DDMmDEDq1evxrp167DXXnulo+lJkUS8MbgeaG5uxpFHHolZs2bhrbfewpVXXolPP/0Uzz//PNra2jBq1Ch89NFHKC0tTXWb+4XL5UJubi5aWlqQk5OT7uYQERERUQbxer3YunUrxowZA5vNlu7mUBJ682/Ym2yQ9AhVXl4e3nvvPaiqioaGBvz617/GY489BgA4++yzsXbt2kETpoiIiIiIiJLRp4V9c3NzsWjRIixatAgNDQ3QNA3FxcWQh0DlESIiIiIiou70Kfk88sgj4cdFRUUoLS2NClObN2/GX//6Vzz99NNwu919uRQREREREVHG6VOgeumll+DxePDpp592qt7x0Ucf4eCDD8b69euRm5uLv/zlL/jmm2/61FgiIiIiIqJM0qdAVVNTg1GjRmHixIkYPXo0fvOb34T33X///fD7/bj33ntx4okn4pZbbsHGjRvR2tra50YTERERERFlgqQD1ccff4wffvgBRUVFOOWUU3D00UfjkUcewSuvvAIA2LJlCwCgoqIi/JyTTjoJS5Ys6WOTiYiIiIiIMkPSRSmuueYaPPTQQ7jgggvC21avXo17770XJ598MrxeLwBE3VNlNps57Y+IiIiIiIaMpEeovF5vVJgCgOnTp8PlcgEANE2D2Wzu9Lxvv/022UsSERERERFllKQDlaZp0DQtatvGjRuj9judzk7PC00FJCIiIiIiGuySnvJ32GGHYe7cubjwwgthsViwYcMGPPDAAxg/fjxqampQV1eHwsLCqOesXLkybsgiIiIiIiIajJIOVH/4wx8wZcoUzJ8/HwAghMCcOXPwt7/9DYcddhhaWlpwwAEH4Mwzz8Rll10Gu92OK6+8Escff3zKGk9ERERERJROSQeq4uJifPrpp3j00Uexbds2HHbYYTjnnHNgsVjw8ccf47///S/OPPNMfPHFFzjjjDOwc+dOFBcX4/rrr09l+4mIiIiIiNJGEkKI/r5Ie3s7XnnlFcyYMQN77LFHf18uKS6XC7m5uWhpaUFOTk66m0NEREREGcTr9WLr1q0YM2YMbDZbuptDSejNv2FvskGfFvbtyqJFi1BfXw8AcDqdOOusszI2TBERERERESUj6Sl/IQ0NDfB4PIgc6BJCwOl04sILL8Srr77a10sQERERERFlpKQD1WeffYaTTjoJO3bsSHiMw+FI9vREREREREQZL+lA9bvf/Q7Nzc04/vjj0d7eDl3Xw1P6hBBYuXIl7rzzzlS1k4iIiIiIKOMkfQ/Vpk2b8O233+K1117D888/jwMPPBBLlizBkiVL8MQTT+CEE07AoYcemsq2EhERERFRhtuyZQtOO+00lJSUwG63Y8aMGfjggw86Hffjjz/izDPPREFBAWw2Gw455BD84x//wADUzEuppAPVnnvuidLSUgBAUVERGhsb0dzcHN5/2mmn4aabbupzA4mIiIiIaHDYtm0brr32Wpx99tl48803ccstt2DdunU45phj8MMPP4SPa25uxsyZM/HSSy8hKysLmqbh888/x0UXXYQrrrgija+g95IOVG63G19//XX467POOgtXXXVV+OvvvvsubhIlIiIiIqKeEZoGoevQA34IXYfQtHQ3qUvLly/HCy+8gLlz5+Lwww/HzTffjOuvvx4ejyeqWN1tt92Gn//856itrcX27dvR1NSEX/3qVwCAhx9+GBs3bkzXS+i1pAPVggULcOCBB8Jms+G5557Dz372M3z33XeYNGkSTjrpJFxyySXIzs5OZVuJiIiIiIYNoetwV+9E46fr0PjpejR+ug7uXVUQup7upiV03nnnwWKxRG2bNm0aAGCvvfYKb5NlGYsWLUJ+fj4AICsrC48++mj4lqHBFKiSLkpxxRVXoKGhAcuWLUNhYSEA4Omnn8acOXPw8ccfw2q14k9/+lPKGkpERERElKmEEEAKg44QAp5dVXBX7+zYpmlwVxkVtu1lFZAkKTUXk+XUnSuOr7/+Gj/96U9xwgknhLfdd999cZoh44gjjsCGDRsG1fq1SQcqVVVx88034/bbbw9vGzt2LL799lt8+eWX2HPPPcNBi4iIiIhoSNN1NHy8NiWnkkwmFB4yAZ7aXXH3e2qq4SivRONnH0Ooap+vVzRhCqAofT5PPJ999hlefvll/O9//4sKbUqC67W2tmLffffF5MmT+6U9/SHpKX9z5szB0Ucf3Wm7zWbDxIkTGaaIiIiIiJIgmy3QA4GE90sJTYOuBiCbLXH3Z4KPPvoIF154ISZPnow1a9Zg9uzZqK6u7vI5fr8fb775JhYvXtyvI2aplvQI1RdffIETTzwxlW0hIiIiIhqcZNkY6UkVSYKkKHFDlaQokM0W5B8wPjXXkpMeY0lowoQJqKysxGGHHYa77roLn3zyCU477bQui9Y9+OCDOOecczB79uyUt6c/Jf3du+SSS3DWWWd1eczcuXOTPT0RERER0aAhBQNQqj4gBOxlFXGvZS+rAIRI3fX6YTRIURSMGDECl112GdatW4e8vDysXr06qnR6pE8++QSbN2/G3XffnfK29LekR6guvvhi3HffffB6vTjkkEOi9mmahtWrV+P//u//+to+IiIiIqJhR1IUOCpGADDumRKaBklRYC+rgKNiBKR+GFXqLyNGjMA555yDBx54AHV1ddhzzz2j9m/duhVLly7FI488kqYW9k3SgWrSpEnYvXs3Fi9enMr2EBERERERAEmW4SivhKNiRDhQQYhBFaZC9tlnHyiKgn322Sdq+9atW/H444/jvvvuS1ioItMlHajmzp2LDz/8EBMmTIDZbO60/4cffuDCvkREREREfSAFQ8ZgDFGRPv30U5x99tkoKCgIb/vyyy+xbNky3H777ZAjXp/P58Odd96JSy65BCNGjEhHc3sl6UB1yimn4JJLLsGkSZMSHjNu3LhkT09ERERERIOIruu4+uqr4XQ6cfnll6OyshIA8Nxzz2Hr1q1YtmxZ+Nh33nkHp512GkpKSrB06dLwdk3TUFNTgwMOOAB33XXXQL+EpCQdqI455hi43e4uj3njjTeSPT0REREREQ0ikiShubkZzzzzDB544AHMmDEDe+yxB6ZMmYK3334bJpMRPd5++22ccMIJUFUVTU1Ncc+1YMGCgWx6nyQdqCwWC7Zs2YLLL78cDQ0NeOuttwAA9957L5xOJy677DKMHTs2ZQ0lIiIiIqLMJUkSnnrqqW6PO/bYYxEIBAagRQMj6cmYn3zyCSZPnoxnn30WmzdvDm+//vrrUV1djVmzZqG1tTUljSQiIiIiIspESQeq3/3ud9hzzz3x4IMPoqioKGrf73//e2zYsAE33HBDnxtIRERERESUqZIOVF988QXee+89XH755cjKyoraZ7PZUFJSghdffLHPDSQiIiIiIspUSd9DNX78eBQWFsbd19jYiJ07d8Ytp05ERERERDRUJD1CVVhYiJaWFgCAECJq37XXXgtVVXHYYYf1rXVEREREREQZLOlA9Zvf/Abz5s3D559/DgDwer1YvXo1TjzxRDz11FOQZRkLFy5MWUOJiIiIiIgyTdJT/iZPnowrr7wSxxxzDOrr6+F0OgEYo1XZ2dl46KGHcNRRR6WsoURERERERJkm6UAFACeeeCKOOeYYvPPOO9i0aRM0TcOYMWNw7LHHIjc3N1VtJCIiIiIiykhJB6pnnnkGZ511Fmw2G0444QSccMIJqWwXERERERFRxkv6HqpLLrkEb7/9dirbQkRERERENKgkHagCgQAefvhhzJkzB//+97+h63oq20VERERERJTxkg5UF1xwAV577TW8+OKL+P777zFz5kzcd9994VLqREREREREQ13SgeqRRx4BABQUFODGG2/EypUrMXLkSMybNw9XXHEFtmzZkrJGEhERERERZaKkA1UsRVEwf/58nHfeeXjppZcwbtw4/PznP0/V6YmIiIiIiDJO0oHq1VdfDT92uVz485//jDFjxuCXv/wlGhoacMYZZ+C2225LRRuJiIiIiIgyUtJl0y+44AJomoYVK1bgiSeeQGtrK3Jzc3HttdfiyiuvxIgRI1LZTiIiIiIiooyTdKDavXs35s+fDyEERo8ejdtvvx0XXnghsrKyUtk+IiIiIiIahHw+H5588kmsXLkSI0aMwOjRo3HppZcmPP67777DpEmTcNVVVw2qmW5JByoAGDduHBYuXIhTTz0Vspyy27GIiIiIiGgQW7NmDc466yycdtpp+Pvf/w6Hw9Hl8S6XCyeeeCKam5sHpoEplHQKys/Px+rVq3HaaaclDFNnnXVW0g0jIiIiIhrudE2D0HVofj+ErkPXtHQ3qVsvvfQSZs+ejVtvvRX33HNPt2FK13WcddZZOP744weohamVdKB69913kZeXl3D/xo0b8dJLLyV7eiIiIiKiYU1oGtq3/4ja1atQt3oValevQvv2HyEyOFStWLECZ555Jn7961/jnHPO6dFzbrzxRsyaNQsnnHBCP7eufyQdqA455JC429va2nD33Xdj+vTp8Pv9yZ6eiIiIiGjQEEJA17TUfagq2n7chrZtWyFU1biGqqJt21a0bf8Ruqqm7FpCiJR8D7xeb7imQk/vgVq6dCkaGhpw3XXXpaQN6dCne6gi1dbW4v7778fixYvR0tICIQQkSUrV6YmIiIiIMpbQddSufD8l55LNZhRPnY72qp1x97fv3AHnqNGoX7MaeiDQ5+uVzjoCkqL0+TzPPvsstmzZgtNPPx3/+Mc/sGHDBnz++ecYMWIEfve73+GII46IOv7jjz/GU089hddff73P106nPleS2Lx5M371q19hjz32wL333guXy4UjjzwSl19+OQtVEBERERH1kmyxQPf7wyNTsYSqQvf7IVssA9yyrj3//PMAAJvNhtNOOw1Lly7FG2+8gerqahx11FFRtwPt2rUL11xzDZYuXQpLhr2O3kp6hGrNmjW499578frrr0PXdVgsFlx11VW4/PLLseeee4aPISIiIiIa6iRZRumsI1J3PkmCZDLFDVWSyQTFakXh4RNTc60UDYJs3LgRAHD77bdj1KhRAIDRo0dj8eLF/7+9Ow9vqk77P/5J0qShhbbUAopQFpGyiczjUrZSVBaVVXBjKgKKKyiMy4z8RBYVF5hRQeUBHGkFiqCADILLMygUB2QoFRhgBMehQgHL0kJb2qZLcn5/YDNkmlaatiSF9+u6znXZ7/fOyX24aczNOed71L17d40fP15DhgyR0+nU6NGjNW/ePEVFRdXIe/tTlRuqTz/9VDNnztSWLVtkGIaaN2+uZ599VsuXL9cbb7zhEZuamlpjiQIAAACBymQy1chlc2VcTqdCmzXXmZ/Sy82FNmsuwzBkrsH3qwknT56UJDVu3NhjvFu3boqJidH+/fu1d+9erV+/Xlu3btWwYcM84goKCiRJ77zzjpYtW6bx48dr/PjxFyb5ajjvhmrhwoX605/+pH379skwDF199dV67rnnNHLkSAUFBWnVqlW1mScAAABwyTBbLKof3ULS2XumjNJSmYKCFNqsueq3aCGTObCaKUmKjIxUZmamCgsLVa9ePY+5tm3bav/+/SosLFReXp5yc3OVm5vrdT9ZWVnKyspyN2iB7rzP7506dUqnT5+WYRh67bXXtH//fo0ZM0ZBQTW2rgUAAACAX5gsFoVGt1CTHnFq3CNOTXrEKTQ6MJspSYqLi5MkpaWllZuzWCwKCgpS+/btNW3aNBmGUW7bsGGDJGnq1KkyDOO8Vwr0t/NuqJ5++mmlp6dr3rx5+uCDDzR27Filp5c/BQkAAACgZpgtFpnMZllsNpnM5oC7zO9cEyZMkCQlJSV5jDudTu3cuVMjRoxQeHi4HzKrXVW6A81ms+nhhx/W7t271bdvX917770aM2aM/v3vf9dWfgAAAADqgB49euiFF17QsmXLtGzZMklnn8/1wgsvKDg4uNx6CxcLn5b0MJvNuueee/T3v/9d9957rx555BH985//LHd67/7776+RJAEAAAAEvhdffFGLFi3Sa6+9ptjYWPXo0UN5eXnasmXLRbGinzcmo4Yejbx161a99tprys7O1uOPP67WrVvrlltuUV5eXk3svtbl5uYqPDxcOTk5CgsL83c6AAAACCAOh0Pp6elq1aqV7Ha7v9OBD6pSw6r0BjX25N2uXbtq9erVmjdvnlatWqWuXbu6lz4EAAAAgItRjTVUZTp06KCPPvpIq1evlslkqundAwAAAEDAqPGGqszgwYN111131dbuAQAAAMDvaq2hkqQPP/ywNncPAAAAAH5Vqw0VAAAAAFzMaKgAAAAAwEdB/k7gfBQVFemDDz7Qpk2b1KxZM7Vo0UKPPfaYR8zWrVs1efJkFRUVqbi4WCNGjNCECRNYGAMAAABArQn4hurbb7/Vfffdp7vvvlsLFixQSEhIuZjPPvtMd955pz7++GMNGDBAp06dUteuXbVv3z7NmzfPD1kDAAAAuBQE9CV/K1euVHx8vKZMmaJXX33VazN16tQpjR49Wv3799eAAQMkSQ0bNtTUqVM1f/58rV69+gJnDQAAAOBSEbANVUpKikaMGKFx48Zp1KhRFcbNnTtXJ06c0MCBAz3G+/XrJ0l65ZVXajVPAAAAAJeugGyoHA6Hxo4dq/r162vatGmVxpadgercubPHeFRUlKKjo5Wamqpjx47VUqYAAAAALmUB2VAtXbpUP/74o/r166f33ntPCQkJ6tSpk2699VZt3LjRHWcYhnbu3ClJio6OLrefyMhISdKuXbvKzRUVFSk3N9djAwAAAICqCMiGavny5ZIku92uu+++W8nJyVq3bp2OHj2qPn36aOXKlZKk7OxslZaWSpLCw8PL7adBgwbuuP/26quvKjw83L01b968tg4HAAAAwEUqIBuqPXv2SJKmT5/uPvPUokULzZ8/X06nU+PHj1dpaamKiorcr7HZbOX2U9ZseZubNGmScnJy3FtGRkZtHAoAAACAi1hANlQnT56UJDVu3NhjvFu3boqJiVFmZqb27t2ryMhImc1nD6GgoKDcfsou4/vv/UhScHCwwsLCPDYAAAAAqIqAbKjK7n0qLCwsN9e2bVv3nN1ud/989OjRcrGZmZmyWCzq0KFDLWYLAAAA4FIVkA1VXFycJCktLa3cnMViUVBQkNq3by9JuuOOOyRJO3bs8IjLzMxUVlaWevbs6W7QAAAAAKAmBWRDNWHCBElSUlKSx7jT6dTOnTs1YsQI9yIUTz75pEJDQ8s9wHfdunWSpOeff77W8wUAAADg6euvv9bAgQP14osvep0/ePCgRowYocjISNntdnXp0kXvvfeeDMMoF+t0OrVgwQLFxsaqV69eio+P15AhQ8qdVPGHgGyoevTooRdeeEHLli3TsmXLJJ1dIv2FF15QcHCw3njjDXfs5Zdfrvnz52vVqlXaunWrJOnw4cN66aWXNHHiRPXt29cvxwAAAABcin766Se9/PLLGjt2rNatWyeXy1Uu5vTp04qLi9PKlStVv359OZ1O7dq1Sw8//LCeeOKJcvFjx47Vyy+/rCVLlmjTpk1KSUnR0KFD1bVrV33zzTcX4rAqFJANlSS9+OKLWrRokV577TXFxsaqR48eysvL05YtWxQVFeURm5CQoBUrVmjixImKj4/XXXfdpSlTpujNN9/0U/YAAABA9blKS2W4XHI6imS4XHL9sop1IGvZsqUmT56smTNnVhgzbdo0DRkyRMeOHdOhQ4d06tQpPfTQQ5Kkd999173qtyQdOHBASUlJmjBhgq6++mr3+JgxYxQdHa233nqr1o7lfAT59d1/RUJCghISEs4rdtCgQRo0aFAtZwQAAABcGIbTqZwfflTej+lylZTIbLWqQZtWioi5WiaLxd/p/arK1jEwm80ejVD9+vU1b948bd++XTt27NCePXvUqVMnSf95pmxOTk65/URERHh9Hu2FFNANFQAAAFAXGIYhw+msyR0q51//Vs73P7iHXCUl7p/Dr75KMplq5K1MFotMNbSvc5U93sibWbNmeY3v3bu3duzYoZYtW7rHO3furKZNm2r27NlKSEhQTEyMJOnnn3/WwYMHlZycXOO5VwUNFQAAAFBNhtOpQ3/5rEb2ZbbZ1Oy2Psr7Md3rfN6P6Qpv20aHP18vV3Fxtd8vesjtMgVd2LbAUsEZtry8PMXExCg2NtY9ZrPZlJycrAEDBujmm2/W6tWr1bFjR82YMUMbNmxwP0bJXwL2HioAAADgUmSxB8tZVCRXSYnXeVdJiVxFxbLYgy9wZrWruLhYn3/+uebPn1/ujFnv3r2VkpKi0NBQDR48WLfccotGjhypjh07+inb/+AMFQAAAFBNJotF0UNur7n9mc0yW61emyqz1SpLPbuuuCmuZt4rQO7HmjNnjkaNGqX4+Hiv86dPn9aSJUsUGRmpwYMHKz4+XgsWLND9999/gTP1REMFAAAAVJPJZKrRy+ZcpaVq0KaVxz1UZRq0aSXD5ZL5Al+mV5vS0tL0ww8/aMGCBV7nly9frrVr12rx4sWSpC1btui2227T6NGj1aBBA91xxx0XMl0PXPIHAAAABBhzUJAiYq5WePu2MlutZ8esVoW3b6uImKsvqmYqPT1dycnJmjt3rtf548eP68EHH/RY0TsiIkKfffaZoqOj9bvf/e5CperVxVMJAAAA4CJislgU3raNItq1dS+bbrhcAXOJXk1IT0/XwoULNWvWrAoXqvjb3/6m/Px8hYSEeIw3bNhQjz76qCZNmqQTJ06oUaNGFyLlcjhDBQAAAAQoc1CQTGazLMHBZ++rqkNnplwul6SzS8p7s3v3bi1ZskTTp0/3aKaKioo0efJkHT58WJLUunVrSdK2bdu8vkfDhg3VsGHDmk7/vNFQAQAAAKhxGRkZkuRujM61fv16xcfHKzk5WR06dFC7du3Url07XX311YqKitL69evVrFkzSVKXLl00cuRIvfnmm0pJSXHvY8+ePZo9e7ZmzpypID82mnWnxQUAAAAQ8I4cOaLhw4dr165dkqSFCxfqu+++08yZM9W3b199+eWXGjhwoEpLS3Xq1Cmv+0hISPD4OTExUZ06ddK4ceNksVjUpEkTWa1WrVixQnFxNbPaoa9MRkXn4C4xubm5Cg8PV05OjsLCwvydDgAAAAKIw+FQenq6WrVqJbvd7u904IOq1LAqvQGX/AEAAACAj2ioAAAAAMBHNFQAAAAA4CMaKgAAAADwEQ0VAAAAAPiIhgoAAAAAfERDBQAAAAA+oqECAAAAAB/RUAEAAACAj2ioAAAAAMBHNFQAAAAA4CMaKgAAAADwEQ0VAAAAAPiIhgoAAAAAfERDBQAAAAA+oqECAAAAAB/RUAEAAACAj2ioAAAAANSI3bt3a9CgQQoLC1NISIi6d++uVatWVRgfHx8vk8nksU2ZMqXS9/jiiy80atQoTZgwQX/605904sSJmj6MKgny67sDAAAAuCikp6erZ8+eKioqUuPGjXXkyBF9++23Gj58uGbNmqVnnnnGI379+vX6/vvvFRMT4x6zWCwaN26c1/0fPXpU9913n0JCQjR//nxdeeWVtXo854szVAAAAECAcpaUyOV0qiS/UC6nU86SEn+nVKGnnnpKzz77rLKzs3Xo0CFlZmZq8ODBkqTnn39e2dnZHvHTp0/Xhg0btG/fPve2d+9eNWnSpNy+9+/fr+uuu06tWrXSp59+GjDNlMQZKgAAACAguUpLdXTrbh3b/r2cRcWyBNt0+fXt1bRbZ5mDAutrvMPhUPv27TV58mT3WKNGjbR06VJdffXV+vnnn/XDDz+oa9euks5etud0OtWoUaNf3ffx48fVp08fNW/eXPPnz5fJZKq14/BFYFUCAAAAqIMMw5CrpLRG9/fztj06unmXe8xZVKwjv/x8+Y2daqyxMFuDqr2v4OBgvfzyy+XGQ0ND1bVrV61evVotWrRwj0+dOlXbtm1TkyZNdN111+mJJ57QyJEjZTaXv4Duqaee0uHDh7V06VIFBVgjKdFQAQAAANXmKinV9jeW1Mi+guoFq8tjd+nY9u+9zmdu/15XxF6jnf/7sUoLi6r9ftc/dZ8sNmu19lG2oIQ3eXl56tu3r6644gpJ0pEjR9SxY0c1adJEW7duVVpamkaPHq1FixZp5cqVioiIcL/2wIEDSk5OVps2bZSRkaExY8Zo9+7dstlsGjVqlB555JFq5V0TuIcKAAAACCDW+iEqKXDIWVTsdd5ZVKzSQoes9UMucGZVd/LkSaWmpurtt992j1155ZVauHCh1qxZo2PHjunDDz9Us2bN9PXXX+uee+7xeP3y5cslSVFRUWrTpo0SExOVkpKili1b6tFHH9XEiRMv5OF4ZTIMw/B3EoEgNzdX4eHhysnJUVhYmL/TAQAAQABxOBxKT09Xq1atZLfby83X9CV/JotZ381Z5rWpsgTb9D9P3ivD6aqR96qJS/4qMn78eF177bV66KGHKo07dOiQevXqpYMHDyolJUW9evWSJCUkJGjp0qVKSkrSqFGj3PEFBQVq1qyZTp06pd27d6tTp06/msuv1fBcVekNOEMFAAAAVJPJZJLFZq2xzXC5dPn17b2+1+XXt5fhctXYe9VWM7V27Vpddtllv9pMSVJ0dLTmzJkjSfr73//uHj958qQkqXHjxh7xISEhuvvuuyVJX331VU2l7BPuoQIAAAACjMVqVdNunSWdvWfKc5W/a2UOsvg5w8pt375daWlpmj59+nm/ZsCAAbLb7R5njyIjIyVJhYWF5eLbtm1b4dyFREMFAAAABCBzUJCu6HqNmna/Vs6iElmCrTKcroBvptLS0rRhwwZNnTq1Sq8zm82yWq266aab3GNxcXFatmyZ0tLSNGzYMI94i+Xsn8M111xT/aSrgUv+AAAAgABlsVpltlhkDbHLbLFUezW+2rZx40Z9++23evbZZz3Gz5w5oyeffFIOh6PC165fv15Dhw71uB8qISFBjRo1UnJyskpLPe9R2759u1q3bq3+/fvX7EFUEQ0VAAAAgGpbsmSJBg8erHfeeUft2rVzb23atFHjxo11/Phx2e12vfzyy7r77ru1a9d/nrG1efNmffnll1qwYIHHPsPDw7Vo0SIdPXpUEydOlMt1diGOzz77TGvWrNGSJUv8/mwqLvkDAAAAUC3vv/++xo4dK0nav3+/15iEhARJUsuWLZWYmKjY2Fj17NlT11xzjfr166c//vGPXl9366236ptvvtHzzz+vLl26KCIiQo0aNdKWLVvUsWPH2jmgKmDZ9F+wbDoAAAAqUpUltxGYWDYdAAAAAAIMDRUAAAAA+IiGCgAAAAB8REMFAAAAAD6ioQIAAAAAH9FQAQAAAICPaKgAAAAAwEc0VAAAAADgIxoqAAAAAPARDRUAAAAA+IiGCgAAAAB8REMFAAAAAD6ioQIAAAAAH9FQAQAAAICPaKgAAAAAwEc0VAAAAADgIxoqAAAAADWmtLRUbdq0kclk8tgWLlxYLnb79u367W9/q4ceeqjC/WVnZ+uRRx7R5ZdfLpvNpnbt2un1119XaWlpbR7GeQvydwIAAAAALh5JSUkqLCxUTEyMeywsLEwJCQnun7OysrRw4UItXrxYu3fv1qhRo7zuq6SkRP369dOOHTvUtGlTmc1m7d+/X88995w2b96sv/zlLzKZTLV+TJXhDBUAAAAQoIodxXKWOJV/Ol/OEqeKHcX+TqlSJSUlmj17tnbu3Kl9+/a5t23btik4ONgdd9lll+nZZ5/1etbqXO+++65atWqljIwMZWRkKC8vT1OmTJEkffrpp1q3bl2tHs/54AwVAAAAEIBKi0v07cq/KfXTrXLkO2QPteuGwV3V4844Bdms/k7Pq/fff1/t2rWT1Xp++UVGRlY6f/jwYS1fvlxm89nzQFarVdOnT9fOnTu1Zs0a7dmzRwMHDqx23tVBQwUAAABUk2EYKikqqbn9uVza+skWfbNso3vMke/QNx+e/bnr0O4ymWvmYjNrsLVGLpsrKirSK6+8ooyMDK1cuVJxcXF6+umnNXjw4ApfY/6VY3j99de9xtxyyy1as2aNWrZsWd20q42GCgAAAKimkqISzbzr5RrZV0hYiMa//5RSP93qdT51zVZ1G9ZT7zz4hgpyC6r9fr//eLJsdlu197N//37dfPPNyszM1NatW7Vp0yZt2rRJ9957rz744APZbFV/D4vF4nU8Ly9PkZGRfj87JXEPFQAAABBQQhvWV0FOvhz5Dq/zjnyHCnLyFdqw/gXOrHKdO3dWUlKSvvjiC508eVJz585VRESEli1bpieeeKJG3+uTTz7Rm2++qfr1/f9nwBkqAAAAoJqswVb9/uPJNbY/i8Use6jda1NlD7WrQWQDjfnjwzXyXtbgmr8fKygoSI899pi6d++u3r1767333tOkSZNq5BK9FStWKCYmRvfff3/1E60BNFQAAABANZlMphq5bK5MsaNYNwzu6r5n6lw3DO4qp9NVo+9XW6699lpNnz5dEyZMUGpqarUbqoMHD2rFihVatGhRzSRYA7jkDwAAAAgwNrtNPe6MU9yI3rKH2iWdPTMVN6K3etzZq040U2WGDx8uSbLb7dXaT1ZWlmbOnKk///nPPt2PVVs4QwUAAAAEoCCbVd2G9VTPu+LlKHDIHmKX0+lUkK1ufYUPDg6WzWZTjx49fN5HVlaWXnvtNc2aNUshISE1mF31cYYKAAAACFA2u00Wq0Wh4aGyWC116sxUmU8++UR/+MMfvD5zyuVySTq77HxFDh8+rFmzZumll17yaKacTqfeeecdbd3qfTXEC6VutbcAAAAAAtK4ceNUWFioF154Qa1atZIkrV27VhkZGZo2bZrX12RkZEg62zR5s3PnTg0aNEh2u12rV692j7tcLp08eVL16tVz78NfaKgAAAAAVFurVq00e/ZsLVu2TDfddJM6dOigYcOG6cUXXywX63Q61atXL+3evVuS9PXXX6tDhw567rnn3Kv3/eMf/1DPnj2Vn59f4XuOGTPmVx8OXNtMRmXn1y4hubm5Cg8PV05OjsLCwvydDgAAAAKIw+FQenq6WrVqVe3FFeAfValhVXoD7qECAAAAAB/RUAEAAACAj2ioAAAAAMBHNFQAAAAA4CMaKgAAAADwEQ0VAAAAAPiIhgoAAAAAfERDBQAAAAA+oqECAAAAAB/RUAEAAACAj2ioAAAAAMBHAd1QlZaWqk2bNjKZTB7bwoULPeK2bt2qPn36KC4uTrGxsXrrrbdkGIafsgYAAABwqQjydwKVSUpKUmFhoWJiYtxjYWFhSkhIcP/82Wef6c4779THH3+sAQMG6NSpU+ratav27dunefPm+SNtAAAAAJeIgG2oSkpKNHv2bO3cuVONGjXyGnPq1CmNHj1a/fv314ABAyRJDRs21NSpU5WQkKBbb71VQ4cOvYBZAwAAALiUBOwlf++//77atWsnq9VaYczcuXN14sQJDRw40GO8X79+kqRXXnmlVnMEAAAAcGkLyIaqqKhIr7zyilasWKHIyEjFx8drzZo15eJWr14tSercubPHeFRUlKKjo5Wamqpjx45diJQBAAAAXIICsqHav3+/br75ZvXv319hYWHatGmThgwZohEjRqi4uFiSZBiGdu7cKUmKjo4ut4/IyEhJ0q5du7y+R1FRkXJzcz02AAAAAKiKgGyoOnfurKSkJH3xxRc6efKk5s6dq4iICC1btkxPPPGEJCk7O1ulpaWSpPDw8HL7aNCggTvOm1dffVXh4eHurXnz5rV0NAAAAMCloaCgQA0bNiy3SnfZZrFYlJWVVe51TqdTy5cv18iRI/X000/rrbfeksPh8JhfsGCBYmNj1atXL8XHx2vIkCHasWPHhTw8rwJ2UYoyQUFBeuyxx9S9e3f17t1b7733niZNmiSbzeaOOfe/y5Q1W97mJGnSpEl66qmn3D/n5ubSVAEAAADVsHTpUp0+fVpNmjRReHi4TCaTe+7nn3/W9ddfr8suu8zjNfv27dO9996r//mf/9GcOXPUsGHDcvsdO3asvvrqK3311Ve6+uqrJUmJiYnq2rWr1q9fr7i4uNo9sEoE5Bkqb6699lpNnz5dhmEoNTVVkZGRMpvPpl9QUFAuvuwSvsaNG3vdX3BwsMLCwjw2AAAAIJAUFjhUUlyi7KxTKikuUWGB49df5Efr1q3T3//+d2VmZmr//v3at2+fe7viiis0cuRIj/jNmzfrhhtu0LBhw7Rw4UKvzdSBAweUlJSkCRMmuJspSRozZoyio6P11ltv1fZhVarONFSSNHz4cEmS3W6X3W5X27ZtJUlHjx4tF5uZmSmLxaIOHTpc0BwBAACAmlBUVKzEeUvV+7qh6v0/Q9X7uqFKnL9URUXF/k7NqzNnzmj69Om68cYby82lpqbq0KFD7u/z0tkzU7fffrv69OmjKVOmVLjfslt4cnJyys1FRER4vf3nQgr4S/7OFRwcLJvNph49ekiS7rjjDr366qvasWOHu7mSzjZTWVlZio+Pdy9OAQAAANQWwzBUWFhzZ49cLpcWLViuebM/cI/l5Z7RvLfO/nz/Q/e4r9aqrnr17B6X5vmqfv365VbfLrN48WINGTLEvc6BYRh6+OGHVVBQoD/96U+V7rdz585q2rSpZs+erYSEBMXExEg6ewnhwYMHlZycXO3cq6NONVSffPKJ/vCHP7ibpCeffFJz5szR6tWrdc8997jj1q1bJ0l6/vnn/ZInAAAALi2FhQ51bX9rjeyrYWS4vti8XMmJK73OJy9cqTGPjNCtPe7RqezyZ22qauv3XygkpF6191OR0tJSLV++XImJie6xDRs26JtvvlGvXr3017/+VZs3b9auXbsUGRmp8ePHe5zJstlsSk5O1oABA3TzzTdr9erV6tixo2bMmKENGzZ4nFjxh4C85G/cuHF64IEHlJ6e7h5bu3atMjIyNG3aNPfY5Zdfrvnz52vVqlXaunWrJOnw4cN66aWXNHHiRPXt2/dCpw4AAABUS1Sjy5SddVp5uWe8zuflnlF21mlFNbrM63yg+fLLLyVJ/fr1c48tX75c0tmVuXv16qVFixbpq6++kslk0p133lnuvqjevXsrJSVFoaGhGjx4sG655RaNHDlSHTt2vGDHURGTYRiGv5P4b3/84x81e/ZsZWVl6aabblKHDh00bNgwdevWzWv8p59+qhkzZig4OFjFxcV66KGH9MADD1TpPXNzcxUeHq6cnBwWqAAAAIAHh8Oh9PR0tWrVSna7vdx8TV/yZw0KUu/rhnptqhqE1dfGtNUq+WVV6+qqqUv+KjJixAg1btxYs2fPdo/16NFDW7Zs0caNGxUfH+8ez8jIUKtWrWS1WpWRkaGoqCj33Pr16xUWFqbIyEgNHjxYBw4c0IIFC3T//fefVx6/VsNzVaU3CMhL/p555hk988wz5x0/aNAgDRo0qBYzAgAAACpmMplq9LK5wgKHEh4Y7r5n6lwJDwxXaamzVi/Tqyl5eXn6y1/+opSUFI/xkydPSiq/Infz5s3Vp08fffnll9q8ebOGDBki6ewZrbVr12rx4sWSpC1btui2227T6NGj1aBBA91xxx0X4Gi8C8hL/gAAAIBLWb0Qux58/D49OnGUGoTVl3T2zNSjE0fpwcfvU72Qys+wBIqVK1cqOjpaN9xwg8d42ZoIhYWF5V5Tdk9U2dzx48f14IMPepxAiYiI0Geffabo6Gj97ne/q630zwsNFQAAABCAgoNtGvPIb7UxbbU2fvcXbUxbrTGP/FbBwTZ/p3beFi9eXO7ZU5LcD+JNS0srN2exWCRJ11xzjSTpb3/7m/Lz8xUSEuIR17BhQz366KM6ePCgTpw4UdOpnzcaKgAAACBA1Quxy2qzKvKyCFlt1jpzZkqSjhw5opSUFCUkJJSbe/TRRxUcHKykpKRyc9u3b1dcXJx7wYnWrVtLkrZt21Yu1uVyqWHDhl4fCHyh0FABAAAAqHHJycnq3r27WrZsWW6udevWevfdd7VlyxbNnDnTPT5//nz961//0sKFC91jXbp00ciRI/Xmm2963Iu1Z88ezZ49WzNnzlRQkP+WhgjIRSkAAAAA1G1LlizR+PHjK5x/8MEHdeWVV2r69OlatmyZQkJC1Lp1a23btk3R0dEesYmJierUqZPGjRsni8WiJk2ayGq1asWKFe7LB/0lIJdN9weWTQcAAEBFqrLkNgJTbS2bziV/AAAAAOAjLvn7L/n5+e6VRc5lsVg8Otn8/PwK92E2m1WvXj2fYgsKClTRScOzzzcI8Sm2sLBQLperwjxCQ0N9inU4HHI6nTUSGxIS4n6oXFFRkUoreVhdVWLr1asns/nsvx0UFxerpKSkRmLtdrv770pVYktKSlRcXFxhbHBwsPs64KrElpaWqqioqMJYm80mq9Va5Vin0ymHo+IHFVqtVtlstirHulwur0ul+hIbFBSk4OBgSWcfrFhQUFAjsVX5veczwnssnxF8RvAZUfVYPiN8i70QnxGGYcjpdFaYh9lsdu/X5XJV+OcbiLGGYVRaN5PJ5PHnUBdjnU6nXC6XCgoKPGro7fe+st+7cgwYhmEYOTk5hqQKt9tvv90jPiQkpMLY+Ph4j9ioqKgKY6+//nqP2BYtWlQY26FDB4/YDh06VBjbokULj9jrr7++wtioqCiP2Pj4+ApjQ0JCPGJvv/32Sv/cznXnnXdWGnvmzBl37KhRoyqNPX78uDv28ccfrzQ2PT3dHfvMM89UGrtnzx537NSpUyuN3bZtmzt25syZlcZu2LDBHfvOO+9UGrt27Vp3bGJiYqWxH330kTv2o48+qjQ2MTHRHbt27dpKY9955x137IYNGyqNnTlzpjt227ZtlcZOnTrVHbtnz55KY5955hl3bHp6eqWxjz/+uDv2+PHjlcaOGjXKHXvmzJlKY++8806Pv8OVxfIZcXbjM+I/G58RZzc+I85ufEac3eryZ0RhYaGxefNmIzU1tcKtoKDAvd8jR45UGntuvj///HOlsbm5ue7YY8eOVRp76tQpd+yJEycqjc3KynLHZmVlVRp74sQJd+ypU6cqjT127Jg7Njc3t9LYn3/+2R175syZSmOPHDniji0oKKg09tChQ+5Yh8PhHv/888/L/Z5U9hmRk5Nj/Bou+QMAAAAAH7EoxS/Kbjw7evSo1xvPOFXvPbaunarnch4u5+FyHu+xfEbwGcFnRNVj+Yz4j0vhM8LhcOjAgQNq0aJFhQsaBNplfFzy5xnrcDj0008/6YorrnD/nkvef+9zc3PVtGnT81qUgobqF6zyBwAAgIqwyl/dxyp/AAAAABBgaKgAAAAAwEc0VAAAAMB54m6Zuqu2akdDBQAAAPyKsgUOKlsYA4GtrHZltawpNFQAAADAr7BarbJYLJWuKInAVlhYKIvF4l6ltKbQUAEAAAC/omwp+ZycHM5S1UFOp1M5OTkeS+bXlKAa3RsAAABwkWrcuLF++uknHTx4UJGRkQoODq7xL+eoWYZhqKioSNnZ2XK5XGrcuHGNvwcNFQAAAHAebDabmjVrppMnT+rnn3/2dzqogtDQUF1++eXuB4LXJBoqAAAA4DyFhIQoOjpapaWlKi0t9Xc6OA9BQUEKCqq9toeGCgAAAKii2v6SjrqDRSkAAAAAwEc0VAAAAADgIxoqAAAAAPARDRUAAAAA+IiGCgAAAAB8REMFAAAAAD6ioQIAAAAAH7F4/i8Mw5Ak5ebm+jkTAAAAAP5U1hOU9QiVoaH6RV5eniSpefPmfs4EAAAAQCDIy8tTeHh4pTEm43zarkuAy+XS0aNH1aBBA5lMpvN6TW5urpo3b66MjAyFhYXVcoaoLdSx7qOGFwfqWPdRw4sDdbw4UMfqMQxDeXl5atq0qczmyu+S4gzVL8xms5o1a+bTa8PCwviLehGgjnUfNbw4UMe6jxpeHKjjxYE6+u7XzkyVYVEKAAAAAPARDRUAAAAA+IiGqhqCg4M1depUBQcH+zsVVAN1rPuo4cWBOtZ91PDiQB0vDtTxwmFRCgAAAADwEWeoAAAAAMBHNFQAAAAA4CMaKgAAAADwEQ0VAAAAAPiIhspHn332mXr27KlevXqpW7duWrJkib9TQgV2796tQYMGKSwsTCEhIerevbtWrVrlNXbr1q3q06eP4uLiFBsbq7feekus2xJ4Nm/erODgYCUlJZWbo4Z1Q1FRkRYsWKD77rtPzz33nP73f/+3XAy1DEw5OTn6wx/+oBtvvFHx8fHq3r27Hn/8cWVmZpaLpYaB4+uvv9bAgQP14osvVhhTlXpRW//4tToePHhQI0aMUGRkpOx2u7p06aL33nuvwtp8//33GjRokHr27Kkbb7xRU6ZMUXFxcW0ewsXJQJUtWLDAqFevnvHdd98ZhmEYP/30k9GoUSPj1Vdf9XNm+G8HDhwwwsLCjODgYKN58+aG2Ww2JBmSjFmzZnnErlu3zqhXr56xdu1awzAMIzs722jbtq3xyCOP+CN1VODQoUNGkyZNDElGYmKixxw1rBu2bNlitG7d2njuueeM/Px8rzHUMjDl5+cbHTp0MPr372+cPn3aMAzDKC4uNh588EGjefPmxokTJ9yx1DAwpKenGy+99JLRqlUrQ5IxdepUr3FVqRe1vfDOp46nTp0ymjdvblitVqN58+ZGUFCQ+zvPuHHjysWnpqYaDRs2NN59913DMAzD4XAYPXv2NG6//XbD6XTW9iFdVGioquhf//qXYbfbjYkTJ3qMz5gxw7BYLEZqaqqfMoM3Q4cONV566SX3l7bjx48bgwcPNiQZNpvNyMrKMgzj7P8MGjVqZAwdOtTj9cnJyYYk45NPPrnQqcOL/Px8o0ePHsa4cePKNVTUsG5YsWKFYbVajaSkpApjqGXgWrhwoSHJ2L59u8f44cOHDUnGnDlzDMOghoHo448/rvCLeFXqRW39q7I6TpgwwRg/fryRnZ1tGIZh5OXlGQ899JC7qdq9e7c7tri42Gjfvr3xm9/8xmMfmzdvNiQZb775Zm0exkWHS/6q6PXXX5fD4dDAgQM9xvv16yen06mZM2f6KTP8N4fDofbt22vy5MkKCQmRJDVq1EhLly7VFVdcoeLiYv3www+SpLlz5+rEiRNe6ypJr7zyyoVNHl49+OCDmjBhgq6//vpyc9Qw8KWkpGjEiBEaN26cRo0aVWEctQxcWVlZks5e9neuiIgISVJ4eLgkahiIIiMjK5yrSr2orX9VVkez2ay3335bDRs2lCTVr19f8+bN029+8xtJ0p49e9yxH330kb7//nsNGDDAYx9du3ZVWFiYZs2apdLS0lo4gosTDVUVuFwurVmzRpLUuXNnj7kuXbrIbDbr888/l9Pp9Ed6+C/BwcF6+eWXy42Hhoaqa9euMplMatGihSRp9erVksrXNSoqStHR0UpNTdWxY8dqPWdUbMaMGWrfvr3uuusur/PUMLA5HA6NHTtW9evX17Rp0yqNpZaBq3///jKZTHr66adVWFjoHv/iiy907bXX6t5775VEDQOR2VzxV76q1Iva+ldldZw1a5bX+N69e0uSWrZs6R6vqI5ms1ldunTR0aNHlZaWVu18LxU0VFVw9OhRHT9+XPXq1VOjRo085oKCghQWFqYzZ87o3//+t58yxLlMJlOFHzx5eXnq27evrrjiChmGoZ07d0qSoqOjy8WW/WvQrl27ai1XVG7NmjX65z//qSlTpnidp4aBb+nSpfrxxx/Vr18/vffee0pISFCnTp106623auPGje44ahnYrrnmGr3++uvauXOn+vbtq+PHj+vHH3/Uhg0btHHjRtlsNmpYx1SlXtQ2sFksFq/jeXl5iomJUWxsrHtsx44dkqhjTQnydwJ1Sdm/uISFhXmdb9CggU6fPq3s7OwLmRaq6OTJk0pNTdW2bdskSdnZ2e7T2mWXq5yrQYMG7jhceHv37tXbb7+tTz/9tMIYahj4li9fLkmy2+26++679cwzz+jgwYMaNGiQ+vTpo+XLl2v48OHUsg549tln1aRJE02ePFmxsbFq1aqVli9f7r7sjxrWLVWpF7Wte4qLi/X5558rOTlZJpPJPV72nZY61gzOUFVBUVGRJMlms3mdL/uQqWgegWHatGmaNWuW2rZtK+k/dZW81466+k92drbGjRunxYsXy263VxhHDQNf2bX706dPd/+LaIsWLTR//nw5nU6NHz9epaWl1LIOMH5Zfvnbb7/V3LlzlZaWpt/85jf67rvvJPH7WNdUpV7Utu6ZM2eORo0apfj4eI/xyr7TUseqo6GqgqioKElSQUGB1/nc3FxJUuPGjS9YTqiatWvX6rLLLtNDDz3kHouMjHRfGuitttTVf6ZOnao9e/aod+/eateunXubNGmSJGnSpElq166dUlJSqGGAO3nypKTyNejWrZtiYmKUmZmpvXv38vtYBzzxxBMqKirSlVdeqdtuu03ffPONiouLdcstt+inn36ihnVMVepFbeuWtLQ0/fDDD5oxY0a5ucq+01LHqqOhqoKrrrpK9evXV3Z2thwOh8dcXl6e8vPzFRUVpaZNm/opQ1Rm+/btSktL0/Tp0z3G7Xa7+2zV0aNHy70uMzNTFotFHTp0uCB54j/y8vKUlZWl/fv3e2xlDxDNzMzU/v37VVRURA0DXNk1+ecuZFCmrHaFhYX8Pga4devW6d1339WQIUPcY507d9a6deuUl5enadOmUcM6pir1orZ1R3p6upKTkzV37lyv89dee62kiusolV+wAhWjoaoCi8WiQYMGyTCMcjfq7d27V5I0YMCASldggX+kpaVpw4YNmjp1qtf5O+64Q9J/btIsk5mZqaysLPXs2bPSpUpRO5KSkmScfV6ex5aYmChJSkxMlGEYGj16NDUMcHFxcZLkddUoi8WioKAgtW/fXhK/j4Hsyy+/lCT3oyjK3HDDDerTp49SU1MlUcO6pir1oraBLz09XQsXLtSsWbMUFOR9uYSK6uh0OrVv3z61bNmShqoK+OZfRb///e9lsVjcy02WWbdunYKCgvT73//eP4mhQhs3btS3336rZ5991mP8zJkzevLJJ+VwOPTkk08qNDTUa10l6fnnn79Q6cJH1DCwTZgwQdLZJvlcTqdTO3fu1IgRI9w3R1PLwNW6dWtJci/qcy6Xy+Wep4aBx+VySfrPPXDnqkq9qK1/VVZHSdq9e7eWLFmi6dOne6z6V1RUpMmTJ+vw4cOSpJEjR6pZs2bl6rhx40bl5+fr//2//1c7B3CxuvDPEq77ZsyYYURERBg//vijYRiG8Y9//MOIiIjgqdIBaPHixUaDBg2MmJgYj+2qq64y6tWrZ9xzzz3u2CVLlhg2m8349ttvDcMwjIyMDKNFixbGxIkT/ZU+KpCYmGhIMhITEz3GqWFge+GFFwyz2Wx8+OGHhmEYhsvlMiZNmmTExMQYJ06c8IilloEpPz/faNeundGpUyfj4MGD7vEPP/zQCAsLM3bs2OEeo4aBJSkpyZBkPPDAA17nq1Ivaus/ldXxr3/9q9GwYcNy33natGlj1K9f34iNjfWI37Bhg2Gz2YwVK1YYhmEYp0+fNq677jpj2LBhhtPpvCDHc7GgofLRwoULjeuuu87o1auXERcXZ6xevdrfKeG//PnPfzYkVbqtWbPG4zVr1qwxYmNjjV69ehldu3Y13n//fT9lj8pU1FAZBjUMdEuWLDGuvfZa48YbbzS6detmjB8/3sjKyvIaSy0D04kTJ4zHH3/cuOqqq4zY2FjjlltuMe6//37jwIED5WKpof8dPnzYiI2NNex2u/v/fV26dDH+7//+r1xsVepFbS+sX6vjF198YQQFBVX6nWfOnDnl9rt582b3d9kbb7zRmDVrllFaWnqhD6/OMxlGBecMAQAAAACV4h4qAAAAAPARDRUAAAAA+IiGCgAAAAB8REMFAAAAAD6ioQIAAAAAH9FQAQAAAICPaKgAAAAAwEc0VAAAAADgIxoqAADOYRiGXC6Xv9MAANQRNFQAgEvemTNn1KVLF11++eWyWq36+OOP/Z0SAKCOoKECAFzy6tevr9TUVN19991yOp2KjY31d0oAgDqChgoAAElWq1UZGRm68sor1bJlS3+nAwCoI2ioAADQ2XunvvnmG/Xs2dPfqQAA6hAaKgAAJO3Zs0dZWVmKi4vzdyoAgDqEhgoAAEkpKSmSxBkqAECVBPk7AQAAAsGmTZsUHh6ua665RpJ0/PhxTZ06VRaLRSdOnNCiRYsUHBzs5ywBAIGGM1QAAOhsQ9WtWzeZzWZlZGToxRdf1KuvvqrCwkJ99NFH2rt3r79TBAAEIM5QAQAuefv27dOxY8fUs2dPHTp0SG+99ZbeeOMN2Ww2nTp1St26dVPHjh39nSYAIADRUAEALnmbNm2SJJnNZr3xxhuaOXOmbDabJGnVqlX+TA0AEOC45A8AcMlLSUlRUFCQ3n77bTmdTm3ZssXfKQEA6ggaKgDAJS8lJUVxcXE6cuSIevfurQEDBuipp57yd1oAgDqAhgoAcEn797//rSNHjuimm26SyWTS8OHD1b9/f73//vvumKVLl/oxQwBAIKOhAgBc0srun7r55pvdYw6HQ40bN5YkFRUVaePGjf5IDQBQB9BQAQAuaSkpKQoNDdWNN97oHouKilJERIQkafHixUpISPBTdgCAQEdDBQC4pOXn52v06NGyWq3usddee01Wq1WjR49WXl6e4uPj/ZghACCQmQzDMPydBAAAAADURZyhAgAAAAAf0VABAAAAgI9oqAAAAADARzRUAAAAAOAjGioAAAAA8BENFQAAAAD4iIYKAAAAAHxEQwUAAAAAPqKhAgAAAAAf0VABAAAAgI9oqAAAAADARzRUAAAAAOAjGioAAAAA8BENFQAAAAD46P8DLPeQ9MhaY0cAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "'created' timestamp seems very low; regarding as unix timestamp\n",
      "'modified' timestamp seems very low; regarding as unix timestamp\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# Set font size\n",
    "matplotlib.rcParams[\"font.size\"] = 16\n",
    "\n",
    "plot_data = moe_data.copy()\n",
    "# Replace k = -1 with infinity\n",
    "plot_data[\"k\"] = plot_data[\"k\"].replace(-1, np.inf)\n",
    "plot_data[\"num_params\"] = plot_data[\"num_params\"] / 87456000\n",
    "\n",
    "# Plot line plot for accuracy\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.lineplot(\n",
    "    data=plot_data,\n",
    "    x=\"k\",\n",
    "    y=\"average\",\n",
    "    hue=\"gate_k\",\n",
    "    marker=\"o\",\n",
    "    legend=\"full\",\n",
    ")\n",
    "# plot the baseline of individual models 90.3\n",
    "plt.axhline(y=90.3, color=\"k\", linestyle=\"--\")\n",
    "plt.axhline(y=48.2, color=\"k\", linestyle=\"--\")\n",
    "\n",
    "plt.xlabel(\"$k$\")\n",
    "plt.ylabel(\"Average Accuracy\")\n",
    "plt.legend(title=\"$k_{gate}$\", loc=\"lower right\")\n",
    "plt.savefig(\"clip-vit-b-32_line-acc.pdf\", bbox_inches=\"tight\")\n",
    "plt.show()\n",
    "\n",
    "# Plot line plot for number of parameters\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.lineplot(\n",
    "    data=plot_data,\n",
    "    x=\"k\",\n",
    "    y=\"num_params\",\n",
    "    hue=\"gate_k\",\n",
    "    marker=\"o\",\n",
    "    legend=\"full\",\n",
    ")\n",
    "plt.xlabel(\"$k$\")\n",
    "plt.ylabel(\"Normalized Number of Parameters\")\n",
    "plt.axhline(y=1, color=\"k\", linestyle=\"--\")\n",
    "\n",
    "plt.legend(title=\"$k_{gate}$\", loc=\"lower right\")\n",
    "plt.savefig(\"clip-vit-b-32_line-params.pdf\", bbox_inches=\"tight\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_281910/1065793999.py:17: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value 'Dense' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.\n",
      "  plot_data.loc[plot_data[\"k\"] == -1, \"k\"] = \"Dense\"\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.legend_handler import HandlerPathCollection, HandlerLine2D\n",
    "\n",
    "matplotlib.rcParams[\"font.size\"] = 15\n",
    "\n",
    "colors = [\n",
    "    \"#EA6B66\",\n",
    "    \"#7EA6E0\",\n",
    "    \"#97D077\",\n",
    "    \"#FFB570\",\n",
    "    \"#CCCC00\",\n",
    "    \"#000099\",\n",
    "    \"#FF99FF\",\n",
    "    \"#666666\",\n",
    "    \"#CCCCCC\",\n",
    "]\n",
    "plot_data = moe_data[moe_data[\"gate_k\"] == 16].copy()\n",
    "plot_data[\"method\"] = \"Ours\"\n",
    "plot_data.loc[plot_data[\"k\"] == -1, \"k\"] = \"Dense\"\n",
    "plot_data\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(6, 5))\n",
    "# ours\n",
    "ours_scatter = plt.scatter(\n",
    "    plot_data[\"num_params\"] / 87456000,\n",
    "    plot_data[\"average\"],\n",
    "    s=plot_data[\"num_params\"] / 87456000 * 30,\n",
    "    marker=\"o\",  # Marker for \"Ours\"\n",
    "    c=colors[0],\n",
    "    label=\"Ours\",\n",
    ")\n",
    "plt.plot(\n",
    "    plot_data[\"num_params\"] / 87456000,\n",
    "    plot_data[\"average\"],\n",
    "    c=colors[0],\n",
    "    # dashed\n",
    "    linestyle=\"--\",\n",
    ")\n",
    "\n",
    "# baselines\n",
    "baseline_scatters = []\n",
    "for i in range(len(baselines[\"method\"])):\n",
    "    scatter = plt.scatter(\n",
    "        baselines[\"num_params\"][i] / 87456000,\n",
    "        baselines[\"average\"][i],\n",
    "        label=baselines[\"method\"][i],\n",
    "        s=baselines[\"num_params\"][i] / 87456000 * 30,\n",
    "        c=colors[(i + 1)],  # Cycle through colors\n",
    "    )\n",
    "    baseline_scatters.append(scatter)\n",
    "\n",
    "# plot the average accuracy of individuals as a horizontal line\n",
    "plt.axhline(y=90.3, color=\"k\", linestyle=\"--\")\n",
    "plt.scatter([8], [90.3], color=\"k\", marker=\"x\", label=\"Individuals\")\n",
    "plt.axhline(y=48.2, color=colors[1], linestyle=\"--\")\n",
    "\n",
    "plt.xlabel(\"Normalized Number of Parameters\")\n",
    "plt.ylabel(\"Average Accuracy\")\n",
    "plt.legend()\n",
    "\n",
    "plt.savefig(\"clip-vit-b-32_scatter.pdf\", bbox_inches=\"tight\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
